mHealth Israel_Connecting time-dots for Outcomes Prediction in Healthcare Big Data_Robert Moskovitch, PhD, Ben Gurion University of the Negev
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Presentation by Robert Moskovitch, PhD, Complex Data Analytics Lab, Software and Information Systems EngineeringBen Gurion University of the Negev. Presentation title: Connecting time-dots for Outcomes Prediction in Healthcare Big Data. Deep dive into BGU data science research for Healthcare.
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The Particle Swarm Optimization (PSO) Algorithm is one of swarm intelligence optimization algorithms.
Usually the population’s values of PSO algorithm are random which leads to random distribution of
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Jmessp13420104
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⭐⭐⭐⭐⭐ Finding a Dynamical Model of a Social Norm Physical Activity Intervention
✅ Low levels of physical activity in sedentary individuals constitute a major concern in public health.
✅ Physical activity interventions can be designed relying on mobile technologies such as smartphones.
✅ The purpose of this work is to find a dynamical model of a social norm physical activity intervention relying on Social Cognitive Theory, and using a data set obtained from a previous experiment.
✅ The model will serve as a framework for the design of future optimized interventions. To obtain model parameters, two strategies are developed: first, an algorithm is proposed that randomly varies the values of each model parameter around initial guesses.
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This document proposes a methodology to analyze time-series data from cardiac implantable devices in order to optimize patient follow-up. The methodology involves (1) fuzzy coding of the time-series data, (2) applying multiple correspondence analysis to reduce dimensionality and identify clusters, and (3) clustering patient trajectories on the factorial planes to compare their evolution patterns to medical records. The methodology was tested on simulated data and applied to data from 41 cardiac resynchronization therapy patients, identifying two areas on the factorial plane correlated with health degradation and stable clinical state.
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The Particle Swarm Optimization (PSO) Algorithm is one of swarm intelligence optimization algorithms.
Usually the population’s values of PSO algorithm are random which leads to random distribution of
search quality and search velocity. This paper presents PSO based on uniform design (UD). UD is widely
used in various applications and introduced to generate an initial population, in which the population
members are scattered uniformly over the search space. In evolution, UD is also introduced to replace
some worse individuals. Based on abovementioned these technologies a Particle Swarm Optimization
Algorithm based on Uniform Design (PSO-UD) algorithm is proposed. At last, the performance of PSOUD
algorithm is tested and compared. Tests show that the PSO-UD algorithm faster than standard PSO
algorithm with random populations.
Recent research in finding the optimal path by ant colony optimization
The computation of the optimal path is one of the critical problems in graph theory. It has been utilized in various practical ranges of real world applications including image processing, file carving and classification problem. Numerous techniques have been proposed in finding optimal path solutions including using ant colony optimization (ACO). This is a nature-inspired metaheuristic algorithm, which is inspired by the foraging behavior of ants in nature. Thus, this paper study the improvement made by many researchers on ACO in finding optimal path solution. Finally, this paper also identifies the recent trends and explores potential future research directions in file carving.
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✅ Low levels of physical activity in sedentary individuals constitute a major concern in public health.
✅ Physical activity interventions can be designed relying on mobile technologies such as smartphones.
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✅ The model will serve as a framework for the design of future optimized interventions. To obtain model parameters, two strategies are developed: first, an algorithm is proposed that randomly varies the values of each model parameter around initial guesses.
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A Non Parametric Estimation Based Underwater Target Classifier
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This document proposes a methodology to analyze time-series data from cardiac implantable devices in order to optimize patient follow-up. The methodology involves (1) fuzzy coding of the time-series data, (2) applying multiple correspondence analysis to reduce dimensionality and identify clusters, and (3) clustering patient trajectories on the factorial planes to compare their evolution patterns to medical records. The methodology was tested on simulated data and applied to data from 41 cardiac resynchronization therapy patients, identifying two areas on the factorial plane correlated with health degradation and stable clinical state.
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Survival Analysis With Generalized Additive Models
Survival analysis is an important method for analysis time to event data for biomedical and reliability applications. It is often done with semiparametric methods e.g. the Cox proportional hazards model. In this presentation I discuss an alternative parametric approach to survival analysis that can overcome some of the limitations of the Cox model and provide additional flexibility to the modeler. This approach may also be justified from a Bayesian perspective and the connection is shown as well. Simulations and case studies that illustrate the flexibility of the GAM approach for survival analysis and its equivalent performance to existing methods for survival data are discussed in the text.
The material presented herein are based on two publications:
1) Argyropoulos C, Unruh ML. Analysis of time to event outcomes in randomized controlled trials by generalized additive models. PLoS One. 2015 Apr 23;10(4):e0123784. doi: 10.1371/journal.pone.0123784. PMID: 25906075; PMCID: PMC4408032.
2)Bologa CG, Pankratz VS, Unruh ML, Roumelioti ME, Shah V, Shaffi SK, Arzhan S, Cook J, Argyropoulos C. High performance implementation of the hierarchical likelihood for generalized linear mixed models: an application to estimate the potassium reference range in massive electronic health records datasets. BMC Med Res Methodol. 2021 Jul 24;21(1):151. doi: 10.1186/s12874-021-01318-6. PMID: 34303362; PMCID: PMC8310602.
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— The healthcare industry is considered one of the
largest industry in the world. The healthcare industry is same as
the medical industries having the largest amount of health related
and medical related data. This data helps to discover useful
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attributes like peripheral blood oxygenation, diastolic arterial
blood pressure, systolic arterial blood pressure, heart rate,
heredity, obesity, and this fitness decision was taken based on
his/her historical and current data. Both the clustering
algorithms were analyzed by applying them on patients current
biomedical historical databases, this analysis depends on the
attributes like peripheral blood oxygenation, diastolic arterial
blood pressure, systolic arterial blood pressure, heart rate,
heredity, obesity, cigarette smoking. By analyzing both the
algorithm it was found that the Density-based clustering
algorithm i.e. the D-stream algorithm proves to give more
accurate results than K-means when used for cluster formation of
historical biomedical data. D-stream algorithm overcomes
drawbacks of K-means algorithm
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We hypothesized that the free cortisol response to waking, believed to be genetically influenced, would be
elevated in a significant percent age of cases, regard less of the afternoon Dexamethasone Suppression Test
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interval in the universe of discourse for forecasting the Longitudinal Dexamethasone Suppression Test (DST)
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throughout the experimental results show that the proposed method gets good forecasting results.
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BPSO&1-NN algorithm-based variable selection for power system stability ident...
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In this paper, the non-invasive
methodology for removing Fetal Electrocardiogram
(FECG) is gained by subtracting the balanced
variation of maternal electrocardiogram (MECG)
movement from the abdominal electrocardiogram
(AECG) banner. The banner assessed from the
mother's guts (AECG) is regularly overpowered by
maternal heartbeat. The maternal portion of the
AECG is the nonlinearly changed variation of
MECG. This paper uses an Adaptive Neuro-Fuzzy
Interference System (ANFIS) structure. It is used
for finding the non-direct change and the ensuing
banner are set up with people based request
figurings. This strategy involves some specific
issues which are a direct result of the low force of
the fetal ECG which is sullied by various
wellsprings of checks. It joins maternal ECG,
electromyogram (EMG) signals, power line
impedances and sporadic electronic upheavals.
Along these lines, we are proposing an improved
multimode PSO estimation for overcoming this
issue. In addition, methods like wavelet change,
flexible filtering, thresholding are moreover used.
We have furthermore empowered the thoracic and
stomach signals using MATLAB programming. It
uses only two signs recorded at the thoracic and
stomach regions of mother's skin. Similarly, our
test shows that the proposed count can expel FECG
banner immediately in pregnancy period and that is
one of the basic focal points of figuring.
Overview
This document discusses the development of a model to predict patient mortality using continuous electrocardiogram (ECG) and laboratory data collected from patients in the pediatric intensive care unit (PICU). Data from multiple sources with different time units were converted to a common 2-minute time frame. Predictive models were developed using time and frequency domain features extracted from the ECG data as well as physiological lab tests. The models provide risk scores and interactive reports in real-time to allow clinicians to monitor patients and update diagnoses continuously. Dimensionality reduction and hierarchical clustering were used to organize and visualize the relationships between high-dimensional patient feature vectors over time.
High precision qt validation
This study compared the precision of semi-automated and high-precision QT interval measurement techniques using data from two thorough QT studies that assessed the effects of moxifloxacin on the QTc interval. Both techniques detected the QTc prolongation induced by moxifloxacin with similar accuracy. However, the high-precision technique improved the precision of QTc measurement by 31% in Study I and 15% in Study II as evidenced by the reduction in the standard deviation of the DQTcF values. More precise QTc measurement could lower the likelihood of false positive results and reduce the necessary sample size in thorough QT studies. Pairwise comparisons found close agreement between the techniques with small mean differences and narrow limits of agreement. Therefore,
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Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
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High resolution mass spectrometry (HRMS) data has revolutionized the identification of environmental contaminants through non-targeted analyses (NTA). However, data processing and chemical identification and prioritization remain challenging due to the vast number of unknowns observed in NTA. The ideal NTA workflow requires harmonized data and tools from a variety of sources to allow the most probable and confirmed identifications. One such tool is the use of chromatographic retention time (RT). Comparing predicted RT of candidate structures to observed RT allows for additional specificity towards ultimate identification. In this work, three RT prediction models were evaluated on the same set of chemicals: 1) a logP-based model, 2) a model generated in ACD/ChromGenius, and 3) a Quantitative Structure Retention Relationship model, OPERA-RT. Our results indicate that both ACD/ChromGenius and OPERA-RT outperform the logP-based model. Between the two, OPERA-RT produced a slightly better fit on the entire set of structures than ACD/ChromGenius (R2 values of 0.85 to 0.83). Further, OPERA-RT, generated within the US EPA’s National Center for Computational Toxicology, predicted 96% of RTs within a 15% (+/-) chromatographic time window of experimental RTs. Finally, to test an NTA workflow, candidate structures were generated for formulae in the test set using the US EPA’s CompTox Chemistry Dashboard and RTs for all candidates were predicted using both ACD/ChromGenius and OPERA-RT. RT screening windows were applied to screen out unlikely candidate chemicals and enhance potential identification. Compared to ACD/ChromGenius, OPERA-RT screened out a greater percentage of the candidate structures by RT, but retained fewer of the known chemicals. This research demonstrates the potential value of including RT prediction in NTA workflows and indicates the potential value of OPERA-RT predictions to support our NTA investigations. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
Assessing the impact of a health intervention via user-generated Internet con...
Assessing the effect of a health-oriented intervention by traditional epidemiological methods is commonly based only on population segments that use healthcare services. Here we introduce a complementary framework for evaluating the impact of a targeted intervention, such as a vaccination campaign against an infectious disease, through a statistical analysis of user-generated content submitted on web platforms. Using supervised learning, we derive a nonlinear regression model for estimating the prevalence of a health event in a population from Internet data. This model is applied to identify control location groups that correlate historically with the areas, where a specific intervention campaign has taken place. We then determine the impact of the intervention by inferring a projection of the disease rates that could have emerged in the absence of a campaign. Our case study focuses on the influenza vaccination program that was launched in England during the 2013/14 season, and our observations consist of millions of geo-located search queries to the Bing search engine and posts on Twitter. The impact estimates derived from the application of the proposed statistical framework support conventional assessments of the campaign.
Survival Analysis With Generalized Additive Models
Survival analysis is an important method for analysis time to event data for biomedical and reliability applications. It is often done with semiparametric methods e.g. the Cox proportional hazards model. In this presentation I discuss an alternative parametric approach to survival analysis that can overcome some of the limitations of the Cox model and provide additional flexibility to the modeler. This approach may also be justified from a Bayesian perspective and the connection is shown as well. Simulations and case studies that illustrate the flexibility of the GAM approach for survival analysis and its equivalent performance to existing methods for survival data are discussed in the text.
The material presented herein are based on two publications:
1) Argyropoulos C, Unruh ML. Analysis of time to event outcomes in randomized controlled trials by generalized additive models. PLoS One. 2015 Apr 23;10(4):e0123784. doi: 10.1371/journal.pone.0123784. PMID: 25906075; PMCID: PMC4408032.
2)Bologa CG, Pankratz VS, Unruh ML, Roumelioti ME, Shah V, Shaffi SK, Arzhan S, Cook J, Argyropoulos C. High performance implementation of the hierarchical likelihood for generalized linear mixed models: an application to estimate the potassium reference range in massive electronic health records datasets. BMC Med Res Methodol. 2021 Jul 24;21(1):151. doi: 10.1186/s12874-021-01318-6. PMID: 34303362; PMCID: PMC8310602.
DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resour...
DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resour...Anjani Dhrangadhariya
PICO recognition is an information extraction task for identifying participant, intervention, comparator, and outcome information from clinical literature.
Manually identifying PICO information is the most time-consuming step for conducting systematic reviews (SR) which is already a labor-intensive process.
A lack of diversified and large, annotated corpora restricts innovation and adoption of automated PICO recognition systems.
The largest-available PICO entity/span corpus is manually annotated which is too expensive for a majority of the scientific community.
To break through the bottleneck, we propose DISTANT-CTO, a novel distantly supervised PICO entity extraction approach using the clinical trials literature, to generate a massive weakly-labeled dataset with more than a million ``Intervention'' and ``Comparator'' entity annotations.
We train distant NER (named-entity recognition) models using this weakly-labeled dataset and demonstrate that it outperforms even the sophisticated models trained on the manually annotated dataset with a 2\% F1 improvement over the Intervention entity of the PICO benchmark and more than 5\% improvement when combined with the manually annotated dataset.
We investigate the generalizability of our approach and gain an impressive F1 score on another domain-specific PICO benchmark.
The approach is not only zero-cost but is also scalable for a constant stream of PICO entity annotations.Computational Pool-Testing with Retesting Strategy
Pool testing is a cost effective procedure for identifying defective items in a large population. It also improves the efficiency of the testing procedure when imperfect tests are employed. This study develops computational pool-testing strategy based on a proposed pool testing with re-testing strategy. Statistical moments based on this applied design have been generated. With advent of computers in 1980‘s, pool-testing with re-testing strategy under discussion is handled in the context of computational statistics. From this study, it has been established that re-testing reduces misclassifications significantly as compared to Dorfman procedure although re-testing comes with a cost i.e. increase in the number of tests. Re-testing considered improves the sensitivity and specificity of the testing scheme.
Patients Classification on Weaning Trials Using Neural Networks and Wavelet ...
The determination of the optimal time of the patients in weaning trial process from mechanical ventilation, between patients capable of maintaining spontaneous breathing and patients that fail to maintain spontaneous breathing, is a very important task in intensive care unit. Wavelet Transform (WT) and Neural Networks (NN) techniques were applied in order to develop a classifier for the study of patients on weaning trial process. The respiratory pattern of each patient was characterized through different time series. Genetic Algorithms (GA) and Forward Selection were used as feature selection techniques. A classification performance of 77.00± 0.06% of well classified patients, was obtained using a NN and GA combination, with only 6 variables of the 14 initials.
PAPER ICIMTH 2014 (GRECIA)
K-MEANS AND D-STREAM ALGORITHM IN HEALTHCARE
K-MEANS AND D-STREAM ALGORITHM IN HEALTHCAREInternational Journal of Technical Research & Application
— The healthcare industry is considered one of the
largest industry in the world. The healthcare industry is same as
the medical industries having the largest amount of health related
and medical related data. This data helps to discover useful
trends and patters that can be used in diagnosis and decision
making. Clustering techniques like K-means, D-streams,
COBWEB, EM have been used for healthcare purposes like heart
disease diagnosis, cancer detection etc. This paper focuses on the
use of K-means and D-stream algorithm in healthcare. This
algorithms were used in healthcare to determine whether a
person is fit or unfit and this fitness decision was taken based on
his/her historical and current data. Both the clustering
algorithms were analyzed by applying them on patients current
biomedical historical databases, this analysis depends on the
attributes like peripheral blood oxygenation, diastolic arterial
blood pressure, systolic arterial blood pressure, heart rate,
heredity, obesity, and this fitness decision was taken based on
his/her historical and current data. Both the clustering
algorithms were analyzed by applying them on patients current
biomedical historical databases, this analysis depends on the
attributes like peripheral blood oxygenation, diastolic arterial
blood pressure, systolic arterial blood pressure, heart rate,
heredity, obesity, cigarette smoking. By analyzing both the
algorithm it was found that the Density-based clustering
algorithm i.e. the D-stream algorithm proves to give more
accurate results than K-means when used for cluster formation of
historical biomedical data. D-stream algorithm overcomes
drawbacks of K-means algorithm
Perceuptal mapping, Factor analysis, cluster analysis, conjoint analysis
The document discusses using clustering analysis techniques to analyze meteorological data from 7 monitoring stations in Toluca Valley, Mexico from 2001-2008. The key findings were:
1. K-means and adaptive clustering algorithms grouped the data into 2 main clusters, rather than the expected 4 seasons.
2. Validation metrics like silhouette coefficient, cohesion, and separation showed higher quality for the 2 cluster solution.
3. This suggests the data from each year had more similar features of 2 seasons rather than 4. Further analysis is needed to understand implications for climate change.
The Cortisol Awakening Response Using Modified Proposed Method of Forecasting...
A growing body of data suggests that a significantly enhanced salivary cortisol response to waking may indicate
an enduring tendency to abnormal cortisol regulation. More methods have been proposed to deal with
forecasting problems using fuzzy time series. In this paper, our objective was to apply the response test to a
population already known to have long-term hypothalamo–pituitary–adrenocortical (HPA) axis dysregulation.
We hypothesized that the free cortisol response to waking, believed to be genetically influenced, would be
elevated in a significant percent age of cases, regard less of the afternoon Dexamethasone Suppression Test
(DST) value based on fuzzy time series and genetic algorithms. The proposed method adjusts the length of each
interval in the universe of discourse for forecasting the Longitudinal Dexamethasone Suppression Test (DST)
data on a fully remitted lithium responder for past 5 years who was asymptomatic and treated with lithium
throughout the experimental results show that the proposed method gets good forecasting results.
Using computable phenotypes in point of care clinical trial recruitment
Using computable phenotypes in point-of-care clinical trial recruitment
The document discusses using computable phenotypes derived from electronic health records to determine patient eligibility for clinical trials at the point of care. It finds that phenotypes can offer the same accuracy as existing archetype-based eligibility criteria and in some cases improve accuracy by leveraging additional clinical knowledge. For phenotypes to be suitable, they must be portable to different datasets and infrastructures, and accurate in identifying eligible patients. The study develops an approach integrating phenotypes with existing trial recruitment platforms and finds phenotypes can identify eligible patients with comparable accuracy to established methods while supporting future trials.
Clinical Database
1. The document describes the development and use of a clinical database to analyze outcomes from cardiac surgeries at Cheng-Hsin General Hospital.
2. Variables were collected from medical records and organized in the database, including demographics, diagnoses, procedure details, and postoperative outcomes.
3. Analysis of the database showed that higher EuroSCORE values, which estimate surgical risk, predicted worse outcomes such as mortality and complications. The database allowed identification of factors associated with postoperative complications.
A Mathematical Bivariate Generalized Poisson Model for Cortisol Awakening Res...
This document discusses a mathematical bivariate generalized Poisson model for analyzing cortisol awakening response (CAR) in patients with multiple sclerosis (MS). It presents the probability generating function (PGF) and moment generating function (MGF) for the bivariate generalized Poisson distribution. CAR is higher in relapsing-remitting MS patients compared to secondary-progressive MS patients and healthy controls. Treated RRMS patients show a higher CAR than untreated RRMS patients. RRMS patients with increased disability scores over time also have a higher CAR. Graphs of the PGF and MGF based on data from RRMS, SPMS and healthy patients support these findings. The model provides a way to analyze circadian cortisol patterns and
Thesis seminar
1. The document discusses implicit shape representations for liver segmentation from CT scans, comparing heat, signed distance, and Poisson transforms.
2. It evaluates these representations using principal component analysis to build a linear shape space model from training data.
3. Results show the Poisson transform provides the most stable and effective implicit representation for segmentation, outperforming other methods in experiments projecting new shapes into the learned shape space.
Deep Learning for EHR Data
Presented a fantastic cutting-edge paper about using deep learning approach to learn from EHR (electronic health record) data in a clinical informatics journal club at UAB, October 2018.
BPSO&1-NN algorithm-based variable selection for power system stability ident...
Due to the very high nonlinearity of the power system, traditional analytical methods take a lot of time to solve, causing delay in decision-making. Therefore, quickly detecting power system instability helps the control system to make timely decisions become the key factor to ensure stable operation of the power system. Power system stability identification encounters large data set size problem. The need is to select representative variables as input variables for the identifier. This paper proposes to apply wrapper method to select variables. In which, Binary Particle Swarm Optimization (BPSO) algorithm combines with K-NN (K=1) identifier to search for good set of variables. It is named BPSO&1-NN. Test results on IEEE 39-bus diagram show that the proposed method achieves the goal of reducing variables with high accuracy.
EUSFLAT 2019: explainable neuro fuzzy recurrent neural network to predict col...
EUSFLAT 2019: explainable neuro fuzzy recurrent neural network to predict col...Servio Fernando Lima Reina
Use of LSTM temporal and frequency analysis capabilities to predict CRC and usage of fuzzy logic to make the system more explainableData Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...
Medical institutions, universities and software giants like Google and Microsoft are dedicating increasing resources to machine learning for healthcare. This is a very exciting but relatively young field. However, best practices for methods and reporting of results are not yet fully established. I have 2.5 years of experience as data scientist at a national cancer center working on clinical data, evaluating external vendors and peer reviewing machine learning in healthcare papers. The talk gives an overview of best practices in prototyping machine learning models on data from the patient electronic health record (EHR). The topics addressed are:1. Introduction to the EHR2. Overview of machine learning applications to the EHR3. Cohort definition for survival problems4. Data cleaning5. Performance metricsExcerpts of papers from renowned institutions will be critically reviewed. The material is intended to be useful not only to machine learning for healthcare professionals, but to practitioners dealing with very unbalanced dataset in the temporal domain. For example, customer churn prediction can be modeled as survival problem.
AN IMPROVED NONINVASIVE AND MULTIMODEL PSO ALGORITHM FOR EXTRACTING ARTIFACT...
AN IMPROVED NONINVASIVE AND MULTIMODEL PSO ALGORITHM FOR EXTRACTING ARTIFACT...IJTRET-International Journal of Trendy Research in Engineering and Technology
In this paper, the non-invasive
methodology for removing Fetal Electrocardiogram
(FECG) is gained by subtracting the balanced
variation of maternal electrocardiogram (MECG)
movement from the abdominal electrocardiogram
(AECG) banner. The banner assessed from the
mother's guts (AECG) is regularly overpowered by
maternal heartbeat. The maternal portion of the
AECG is the nonlinearly changed variation of
MECG. This paper uses an Adaptive Neuro-Fuzzy
Interference System (ANFIS) structure. It is used
for finding the non-direct change and the ensuing
banner are set up with people based request
figurings. This strategy involves some specific
issues which are a direct result of the low force of
the fetal ECG which is sullied by various
wellsprings of checks. It joins maternal ECG,
electromyogram (EMG) signals, power line
impedances and sporadic electronic upheavals.
Along these lines, we are proposing an improved
multimode PSO estimation for overcoming this
issue. In addition, methods like wavelet change,
flexible filtering, thresholding are moreover used.
We have furthermore empowered the thoracic and
stomach signals using MATLAB programming. It
uses only two signs recorded at the thoracic and
stomach regions of mother's skin. Similarly, our
test shows that the proposed count can expel FECG
banner immediately in pregnancy period and that is
one of the basic focal points of figuring.
Overview
This document discusses the development of a model to predict patient mortality using continuous electrocardiogram (ECG) and laboratory data collected from patients in the pediatric intensive care unit (PICU). Data from multiple sources with different time units were converted to a common 2-minute time frame. Predictive models were developed using time and frequency domain features extracted from the ECG data as well as physiological lab tests. The models provide risk scores and interactive reports in real-time to allow clinicians to monitor patients and update diagnoses continuously. Dimensionality reduction and hierarchical clustering were used to organize and visualize the relationships between high-dimensional patient feature vectors over time.
High precision qt validation
This study compared the precision of semi-automated and high-precision QT interval measurement techniques using data from two thorough QT studies that assessed the effects of moxifloxacin on the QTc interval. Both techniques detected the QTc prolongation induced by moxifloxacin with similar accuracy. However, the high-precision technique improved the precision of QTc measurement by 31% in Study I and 15% in Study II as evidenced by the reduction in the standard deviation of the DQTcF values. More precise QTc measurement could lower the likelihood of false positive results and reduce the necessary sample size in thorough QT studies. Pairwise comparisons found close agreement between the techniques with small mean differences and narrow limits of agreement. Therefore,
Similar to mHealth Israel_Connecting time-dots for Outcomes Prediction in Healthcare Big Data_Robert Moskovitch, PhD, Ben Gurion University of the Negev (20)
A comparison of three chromatographic retention time prediction models
A comparison of three chromatographic retention time prediction models
Assessing the impact of a health intervention via user-generated Internet con...
Assessing the impact of a health intervention via user-generated Internet con...
Survival Analysis With Generalized Additive Models
Survival Analysis With Generalized Additive Models
DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resour...
DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resour...
Computational Pool-Testing with Retesting Strategy
Computational Pool-Testing with Retesting Strategy
Patients Classification on Weaning Trials Using Neural Networks and Wavelet ...
Patients Classification on Weaning Trials Using Neural Networks and Wavelet ...
Perceuptal mapping, Factor analysis, cluster analysis, conjoint analysis
Perceuptal mapping, Factor analysis, cluster analysis, conjoint analysis
The Cortisol Awakening Response Using Modified Proposed Method of Forecasting...
The Cortisol Awakening Response Using Modified Proposed Method of Forecasting...
Using computable phenotypes in point of care clinical trial recruitment
Using computable phenotypes in point of care clinical trial recruitment
A Mathematical Bivariate Generalized Poisson Model for Cortisol Awakening Res...
A Mathematical Bivariate Generalized Poisson Model for Cortisol Awakening Res...
BPSO&1-NN algorithm-based variable selection for power system stability ident...
BPSO&1-NN algorithm-based variable selection for power system stability ident...
EUSFLAT 2019: explainable neuro fuzzy recurrent neural network to predict col...
EUSFLAT 2019: explainable neuro fuzzy recurrent neural network to predict col...
Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...
Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...
AN IMPROVED NONINVASIVE AND MULTIMODEL PSO ALGORITHM FOR EXTRACTING ARTIFACT...
AN IMPROVED NONINVASIVE AND MULTIMODEL PSO ALGORITHM FOR EXTRACTING ARTIFACT...
More from Levi Shapiro
Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...
Michigan HealthTech Market Map 2024. Includes 7 categories: Policy Makers, Academic Innovation Centers, Digital Health Providers, Healthcare Providers, Payers / Insurance, Device Companies, Life Science Companies, Innovation Accelerators. Developed by the Michigan-Israel Business Accelerator
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Prix Galien International 2024 Forum Program
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
mHealth Israel_Healthcare Finance and M&A- What Comes Next
Healthcare Finance and M&A, What Comes Next? Presentation by Matthew R. Kittay, National Co-Chair, M&A Practice Group, Fox Rothschild LLP. Includes fundraising and investments. Breakouts by subsector- Healthcare (overall), Healthcare services, Digital health, Biopharma, Pharmatech, Medtech, Healthcare IT. Healthcare transaction distribution breakouts. Exits remain flat. Avoiding common legal pitfalls like IP, compliance, governance structure. Current legislation in health law. IP strategy for healthtech.
Healthcare Market Overview, May 2024: Funding, Financing and M&A, from Oppenh...
Oppenheimer & Co. Inc, co-Head of Healthcare Investment Banking, Michael Margolis, provides H1 Healthcare Financing, Funding and M&A Overview. Table of Contents
1. Broader Market Overview
2. Biotech M&A Market Overview
3. Private Biotech Financing Market Update
4. Key Advice For Healthcare Companies
Current State of Play; Healthcare has Underperformed the Broader Market Over the Last Twelve Months; Signal-to-Noise is Getting Worse; Healthcare IPO Activity has Decreased Significantly Since 20–21 Pandemic Levels; Biotech Financing Activity Has Remained Robust in 2024; Biotech M&A Market Remains Incredibly Active; Biotech M&A Market Remains Incredibly Active; Big Pharma Upcoming Patent Expirations; Since November 2023 Oncology has accounted for over half of all M&A; Oncology, Autoimmune / I&I, and CV & Metabolic Remain the Top Areas in M&A; Small Molecule Beats Out All Other Modalities in M&A Despite IRA Concerns; Value of Big Pharma Acquisitions by Therapeutic Area in Q1 2024; Private Financing Market Update; 2024 Private Placement Activity On Track to Approach, If Not Exceed, 2020 Levels; Oncology, Particularly Solid Tumor, Continues to Attract VC Investors; Despite the IRA, Small Molecules Continue to Attract VC Dollars; Preclinical-Stage Companies Make Up Almost Half of Private Placements in 2023; Valuations by Development Stage – 2023; Typical Biotech Investors Remained Active in Q1 2024; 23 $100M+ Deals were Raised in Q1 2024; Biotech Fundraising Momentum Continued into 2024; Key Advice For Israeli Healthcare Companies; Although Israel has Strong Presence on US Public Markets, There is Room to Grow; Telling Your Story Effectively; Interacting with Investors to Build Long-term Credibility; Seven Simple Rules for Pitch Decks;
Version Bravo- The Springboard for Navy SEAL entrepreneurship, cohort 003
Description of the Version Bravo intensive entrepreneurial launch program for 7 Israeli and 7 US former Navy SEALs. Details about each startup concept, the CEOs, the sector, etc.
Radical Life Extension_Dr. Leon Peshkin_Dec 2023
Presentation for mHealth Israel by Dr. Leon Peshkin, Harvard Medical School, exploring research into Embryology and Longevity, emphasizing Germline and protein aggregates. Includes current overview, anti aging through history, Lifespan Expansion, ALEC: Animal Life Expectancy in Controls, Scalable Platform in Pharmacobiology, Embryos Cleanse Protein Aggregates, Lysosomal switch triggers proteostasis renewal, Xenopus, Rejuvenation Roadmap, Citizen Science Approach to Aging, Xenopus: Maternal Dowry Molecules, Human Disease Modeling
Israel’s Life Science Hub 2023 English Abstract.pdf
The war between Israel and Hamas brings its own set of business
challenges. Challenges that may impact how we communicate with
partners and investors abroad. We should portray the life science sector as resilient and adaptable, even in times of crisis. This document is a a messaging outline for Israel's Life Science Hub despite the war with Hamas. Four key points to emphasize:
1) Global activity (resilience and agility)
2) Continuity of care and preventive medicine
3) World leading clinical trials industry
4) Dynamic scientific, research and entrepreneurial ecosystems
Gil Bashe FINN Partners: The Future of Digital Health – Nose Dive or Transfor...
The Future of Digital Health – Nose Dive or Transformation, by Gil Bashe, Dec 4th, 2023 at the mHealth Israel conference. Digital Health Innovation Ecosystem Investment Trends. Data & Methodology. Digital Health Taxonomy. Key Insights for Digital Health Innovation in H1 2023. Global Digital Health Funding Across Regions. Funding in North America. Shifting Focus in North America Digital Health Funding. Investment Focus for Digital Health Venture Funding. Ventures are turning to partnerships for proof points, scale and funding. 2022 new partnerships. North America digital health investor participation. Most active partners in North America. North America Ecosystem Development. Venture distribution by stage. Funding distribution. Comparison to 2022 Funding. Noteworthy deals, noteworthy exits.
Urgent Request and Call for Action for Ensuring Safety and Inclusivity at MIT
We, 465 MIT Alumni, Staff, and Students, are writing to express our deep concern, fear, and disappointment regarding the recent protest that took place Thursday afternoon, in front of the MIT Stratton Student Center. While we fully support the principles of free
speech and the right to peaceful assembly, it is essential that we also prioritize the safety and well-being of all members of the MIT
community.
During the protest, a particular slogan was prominently displayed and chanted, which has raised significant concerns. The slogan
"From the [Jordan] river to the [Mediterranean] sea, Palestine will be free!" has been a source of contention due to its potential
implications and the real safety risks it poses to Jewish and Israeli students on campus [See video footage attached]. This slogan
has been time and again associated with calls for the destruction of the State of Israel and has been used in contexts that
promote violence, which raises legitimate concerns about the safety and security of our Jewish and Israeli students and staff.
Furthermore, we would like to draw your attention to recent events that demonstrate the potential dangers associated with this
slogan. During the 2023 Israel-Hamas war, British Home Secretary Suella Braverman proposed criminalizing the use of the slogan
in certain contexts, recognizing the potential harm it can cause. Additionally, on October 11, ‘23, Vienna police banned a
demonstration, citing the inclusion of the phrase "from the river to the sea" in invitations, as it was seen as a portrayal of a violation
of Article 2 of the European Convention on Human Rights.
In addition to the use of these derogatory messages, several attendees of the event used hateful wordings and messages towards
Jewish and Israeli bystanders. In one case, a perpetrator aggressively held their bicycles as intended to harm a Jewish MIT student,
stating that “[your] ancestors did not die in the Holocaust so they could kill Palestinians” [See video footage attached]. In another
incident, protesters chanted “one solution, intifada revolution”. In the context of the on-going Israeli-Palestinian conflict, the word
"Intifada" means the armed and violent Palestinian insurrection targeting Israelis, including civilians, which resulted in the killing of
thousands of Israelis in the last few decades.
On Oct. 22nd, a statement by MIT CAA (Coalition Against Apartheid) came to our attention. In this document, MIT CCA states that
they "hold the Israeli regime responsible for all unfolding violence". They later call the October 7th terror attack a "response to
the settler colonial regime", and continue justifying it throughout the document.
In this matter, MIT CAA is justifying the heinous and barbaric crimes committed on Oct 7th. Furthermore, these statements have the
potential to fuel acts of aggression
HLTH-2023-Digital-Catalouge.pdf
Overview of the Israeli exhibitors at the 2023 HLTH conference in Las Vegas. Exhibitors included 6Degrees, AppScent, Belong.Life, Datos, Expecting, IntraPosition, Kahun Medical, Kemtai, Maverick, Neteera, QuantaIX, Respiration Scan, Nerivio, Xoltar.
40% of Israeli technology investment is devoted to Life Science. Within that domain, the largest sector is Medical Devices and Digital Health (over 65 percent of companies). In the medical device arena, Israeli scientists and engineers have integrated advanced technologies in electronics, communications and electro-optics to develop world-class innovations in Digital Imaging, Medical Lasers, Telemedicine, Early Diagnostics,
Smart Surgical Equipment and more. Over 600 medical device exporters engaged in a variety of medical application
such as Cardiovascular and Peripheral Vascular, Neurology and Degenerative Diseases, Preparedness and Emergency
Medicine, Intensive Care, Women Health, Orthopedics and Sport Medicine, Gastrointestinal, Infection Control, Ophthalmology, Pain and Wound Management, Oral and Dental Care, Dermatology and Aesthetics
Baptist Health- Engineering the Future of Healthcare
Presentation by Mark Coticchia, Chief Innovation Officer, Baptist Health, for mHealth Israel community, September, 2023. Baptist Health has internationally renowned centers of excellence in cancer, cardiovascular care, orthopedics and sports medicine, and neurosciences.
A not-for-profit organization supported by philanthropy and committed to its faith-based charitable mission of medical excellence, Recognized by Fortune as one of the 100 Best Companies to Work For in America and by Ethisphere as one of the World’s Most Ethical Companies.Innovation is paramount to health system’s performance and reputation.
Becker’s 2019 Advisory Board survey revealed innovation and technology ranked as the top priority among healthcare finance professionals - up from eighth in 2018. 90% healthcare/life science leaders agree that the pandemic will fundamentally change the way they do business, requiring new products, services, processes, and business models (McKinsey: Innovation Through Crisis Survey). Innovation has been proven to help health systems in many ways. A capability and culture of innovation accomplish numerous goals:
Innovation capability and culture improve the care and work environment. They enhance the reputation through recognition for discoveries made at and through Baptist Health. They aid in the recruitment and retention of top talent. And they help systems harness money that otherwise would be leaving the system – licensing revenues and investment returns and corporate research support and donor revenues. Successful Programs - Common Underpinnings. Innovation as a strategic, institutional priority
Program built on institutional assets and centers of excellence
Experienced, professional team
Technology development and sourcing, Dedicated, long term support. Doing healthcare innovation well at a large enterprise takes a highly specialized team and skill set. Collectively, they need to have deep knowledge of healthcare regulation, medical procedures, patient safety, business development, transactions, business law, innovation markets, entrepreneurship, venture capital, commercialization, tech transfer, organizational change management, and much more. Programs- services, technology management, corporate co-creation, global medical service lines and facilities; Focus on market opportunity vs. technology; Select & concentrate on winners; Operate as a business; Proactive in new company formation; Progress, milestones, preliminary results; Building New Innovation Pathways; Improving Treatment for Cancer Patients; Predicting & Preventing Heart Attacks; Improving Outcomes in Cardiac Care; Enhancing a Culture of Innovation at Baptist Health & South Florida; Cleerly, TriVentures, COTA; Innovation is paramount to health system’s performance and reputation.
Baptist Health has established an innovation function predicated on best practices and tailored to its assets and the opportunities extending from Miami’s economic growth
YEDA Techn Transfer at Weizmann Institute- Discord and Challenges in Academic...
Presentation by Yael Klionsky, YEDA, for the mHealth Israel community in September, 2023. Title: Challenges in Academic Technology Transfer. Examples-
Transplantation Immunology and Immunometabolism. Efranat Pharma was developing an anticancer immunotherapy treatment based on a natural plasma protein molecule. From target discovery to clinical validation. Clinical-stage drug discovery and development company utilizing a broadly applicable, predictive
computational discovery platforms to identify novel drug targets and new biological pathways and develop
therapeutics in the field of cancer immunotherapy. To allow SOCIETY to benefit from discoveries made at the academic institution. To enable SCIENTISTS to transfer their new technologies to the market. To create an additional source of INCOME for the INSTITUTE so that more independent research can be conducted. Three important elements that make an idea patentable:
1) The invention must be new: the same idea can’t have been
published before in any form; 2) There must be some inventive step of ‘non-obviousness’.
This can be hard to define and depends on the context; 3) The disclosure in a patent must be sufficient for a skilled
person to reproduce the invention with only routine effort; Technology Transfer Company - modus operandi; OUR PURPOSE- To provoke transformative scientific breakthroughs that will shape the future of humanity; SCIENTIFIC STAFF- 300 Principal investigators, >2,000 Research students and PhDs; 5 FACULTIES – BASIC SCIENCE, Biology, Physics, Biochemistry, Math/CS
Chemistry; Generated IP- 57% in Life Science & Biotech; Among the Highest
Income per Researcher
Worldwide; 1959 (First TTO outside the US); Today- More applications per PI than in most Ivy league universities; Copaxone- >$30B
ANNUAL SALES BASED ON Weizmann IP; 20 new licenses per year and 10 new companies per annum; www.yedarnd.com
HADASIT: Tech Transfer and More in Life Science
Overview of activities in Life Science of Hadasit, the technology transfer arm of Hadassah Hospital in Jerusalem. Includes details about Jerusalem Biodesign program; spinouts like Brainwatch; details about tech transfer (the Secret Engine Behind Israel’s Success); relationship and examples of TTOs enabling Israel's greatest success stories; contrasting of Adademia (Scientific driven research, Creation of new knowledge, Publication, Sharing of Material, Social responsibilities) and Industry (Applied research & specific objectives, Develop new products, Product development, Secrecy and patent protection, Organization responsibilities); Development gap between initial inventions and product development; the Art of translation (from academic research to medical companies); Tech transfer transforms cutting-edge research into marketable healthcare technologies; LICENSING TO EXISTING COMPANIES; SPINNING OFF STARTUPS; CO-DEVELOPMENT OF JOINT IP; Technology Transfer Offices from Academia/Research Hospitals – to Industry; Overview of Hadassah and Hadasit (TECHNOLOGY TRANSFER COMPANY AND INNOVATION ENGINE OF HADASSAH UNIVERSITY HOSPITALS); Examples of “HADASSAH MADE” PRODUCTS IN THE GLOBAL MARKET; RECENT TECH TRANSFER SUCCESS; Example- Lineage Exclusive Worldwide Collaboration with Genentech Opregen® RPE Cell Therapy for the Treatment of Ocular Disorders; HADASIT PILLARS-
NURTURING INTERNAL INNOVATION, Tech Transfer, EXTERNAL INNOVATION. External- SERVICES & COLLABORATIONS WITH COMPANIES, BIOHOUSE FOR STARTUPS, DIGITAL HEALTH ACCELERATOR); Internal Innovation- NURTURING INTERNAL INNOVATION, HADASSAH SEED FUND, JERUSALEM BIODESIGN PROGRAM; TYPES OF RELATIONS WITH EXTERNAL COMPANIES- CONSULTING, SAB, CLINICAL TRIALS, R&D SERVICES, DATA LICENCE, ALPHA/BETA SITE, PILOTS, DESIGN PARTNERSHIPS.
Presenting to Investors & the Media.pdf
Presenting to Investors and the Media, lecture by Drew Levinson, LifeSci Communications to mHealth Israel. Three sections: Making a good presentation, Handling
interviews with reporters and Answers that resonate. PRESENTING TO INVESTORS AND THE MEDIA- Compelling delivery, Commanding a room, • Lasting Impact. A good presentation includes Information, Motivation and Excitement. Never put them to sleep. Audience impact includes content, credibility and delivery. Decisions are made leading to potential partnerships, winning business, so much more than a deck, your business, your brand, you. How to captivate begins with storytelling and conversation. More than features- benefits, humanize, positive impact. Don't complicate your message with jargon. Feel the passion- contagious, vision, determination. Know your audience- who are they, what do they know about you, how much do they know, interests, concerns. Articulate your vision- see it, feel it, believe in it. Take them on your journey- compelling narrative, make it personal, why are you doing this, inspiration. Your team- experienced, knowledgeable, aligned, execute. Risks and challenges- recognize, address, plan to mitigate. Test drive your room. What does it look like? Where is the podium? Where will I be standing? Where will you be sitting? Feel comfortable. Three parts to attention. The beginning- attention, interest, what's in it for them, entusiasm, preview. The middle- core, insights, challenges, solutions, relatable. The ending- summary, reinforce, messages, benefits, call to action, keep the momentum going. How to answer questions. The Four R's: repeat, reinforce, refer, remember. Talking to reporters- necessity; Good interview can enhance reputation; Bad interview can tarnish reputation; Preparation is vital. Shapes public opinion: Elevates your brand; Establishes authority; Showcases your business; A bridge; Reputation; Trust; Visibility. Know the reporter. Audience; What have they written; Previous stories; Questions asked. Concise- clear, succinct, engaging. Make it relatable: Stories; Anecdotes; Experiences; Examples; Metaphors; Connect. Honesty and transparency. It is okay not to know every answer. You don’t have to answer every question. Control the narrative. What not to do when talking to reporters. Come up with another way to say no comment. What to wear- solid colors, blues and grays, nothing distracting. Expertise, passion, vision, lasting impression, connections. High stakes, high rewards. Preparation; Know your audience; Deliver with confidence; Enthusiasm; Authenticity. Begin the journey. Engage in dialogue; Build relationships; Inspire trust and confidence; Valued; Enlightened; Motivated and excited.
Nissan Elimelech, Founder, Augmedics: How I Built the World's First XR Surgic...
Presentation by Nissan Elimelech, Founder, Augmedics: How I Built the World's First XR Surgical Navigation Company and What's Next for XR. Covers the company founding across multiple milestones and key success factors.
Beyeonics CEO, Ron Schneider, Advances in Medical XR
Overview by Beyeonics CEO, Ron Schneider, about the company. Beyeonics One is the first ophthalmic exoscope with an augmented reality surgical headset. It is a high-definition, fully digital imaging platform enabling surgeons to see a magnified, three-dimensional (3D) image of the surgical field. The small footprint, the fast setup, automation, and zero turnover time between procedures all contribute to the efficiency operating rooms strive for. Over 3000 cases to date. Unconstrained Movement. Unconstrained workflow. Data connectivity. Designed for continuous innovation.
XRHealth Founder, Miki Levy
XRHealth is revolutionizing healthcare, bringing patient care into the Metaverse. Includes a description of the TeleHealth Platform. Lessons Learned – Building the clinical Metaverse. Last mile delivery
Building a product in the Metaverse is easy – getting people to use it is hard. Virtual Care can’t be based only on XR. HMDs bring friction – Charging, Guardian, Safety, Passwords etc. Expanding virtually in a brick & mortar payer environment. Once you cross the chasm – adherence/ satisfaction/retention goes ballistic. Patient Outcomes-
Patients report significant improvement in symptoms following treatment. Adherence - patients follow Home Exercise Plans as prescribed. 92.2% with XRHealth vs 50% with regular treatment. Patient satisfaction - 85 NPS vs 38 NPS in healthcare
93.3% patient retention -complete treatment cycle as prescribed. XRHealth Luna AI Reduces Hot Flashes and Improves Psychological Well-Being in Women with Breast and Ovarian Cancer: A Pilot Study. Virtual reality immersion compared to monitored anesthesia care for hand surgery: A randomized controlled trial. Lessons Learned – Autism Spectrum Disorder. The future of the Mediverse.
Digital Health in US Health Systems.pptx
April, 2023 presentation by Gil Bashe, Global Chair, Health Practice, FINN Partners. Insights and analytics, in collaboration with Galen Growth, tracking Digital Health collaboration, adoption, integration, and best practices across the leading US Health Systems. There is a section about focus areas for digital health in health systems and hospitals. The most active health systems are partnering more in diagnosis and have a higher share of digital tools for research. Comprehensive breakout of digital health activities at the Top 10 players: Mayo, Mount Sinai, Cleveland Clinic, Sloan Kettering, Massachusetts General, Northwell, Cedars Sinai, Brigham & Women's, InterMountain. Global breakout of health systems with digital health partnerships at scale. Geographical breakout of digital health partner headquarters (by region). Strong preference for B2B business model. 1/3 of digital health partnerships with Early Stage venture companies. Emphasis is on strong clinical evidence. Portfolio size allows greater diversity. Cluster distribution depends on therapeutic area. Digital health analytics breakout including alpha score, venture similarity score, venture valuation, team signal, partnership signal, evidence signal.
Course Syllabus (Digital Rosh): The Future of Digital Medicine- Biology, Gene...
Syllabus for the Future of Digital Medicine course, 2023- Biology, Genetics, Technology and BioInformatics. Includes lectures from Noam Shomron, Michal Rosen-Zvi, Eyal Zimlichman, Gila Tolub, Dana Bar-On, Yesha Sivan, Vladi Dvoryis, Varda Shalev, Avi Schroeder, Christian Tidano, Eyal Toledano.
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Recently uploaded
Null Bangalore | Pentesters Approach to AWS IAM
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
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一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理
原版一模一样【微信：741003700 】【(爱大毕业证书)爱荷华大学毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理(爱大毕业证书)爱荷华大学毕业证【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理(爱大毕业证书)爱荷华大学毕业证【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理(爱大毕业证书)爱荷华大学毕业证【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理(爱大毕业证书)爱荷华大学毕业证【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Accident detection system project report.pdf
The Rapid growth of technology and infrastructure has made our lives easier. The
advent of technology has also increased the traffic hazards and the road accidents take place
frequently which causes huge loss of life and property because of the poor emergency facilities.
Many lives could have been saved if emergency service could get accident information and
reach in time. Our project will provide an optimum solution to this draw back. A piezo electric
sensor can be used as a crash or rollover detector of the vehicle during and after a crash. With
signals from a piezo electric sensor, a severe accident can be recognized. According to this
project when a vehicle meets with an accident immediately piezo electric sensor will detect the
signal or if a car rolls over. Then with the help of GSM module and GPS module, the location
will be sent to the emergency contact. Then after conforming the location necessary action will
be taken. If the person meets with a small accident or if there is no serious threat to anyone’s
life, then the alert message can be terminated by the driver by a switch provided in order to
avoid wasting the valuable time of the medical rescue team.
Height and depth gauge linear metrology.pdf
Height gauges may also be used to measure the height of an object by using the underside of the scriber as the datum. The datum may be permanently fixed or the height gauge may have provision to adjust the scale, this is done by sliding the scale vertically along the body of the height gauge by turning a fine feed screw at the top of the gauge; then with the scriber set to the same level as the base, the scale can be matched to it. This adjustment allows different scribers or probes to be used, as well as adjusting for any errors in a damaged or resharpened probe.
Beckhoff Programmable Logic Control Overview Presentation
This presentation is to describe the overview of PLC Beckhoff for beginners
Open Channel Flow: fluid flow with a free surface
Open Channel Flow: This topic focuses on fluid flow with a free surface, such as in rivers, canals, and drainage ditches. Key concepts include the classification of flow types (steady vs. unsteady, uniform vs. non-uniform), hydraulic radius, flow resistance, Manning's equation, critical flow conditions, and energy and momentum principles. It also covers flow measurement techniques, gradually varied flow analysis, and the design of open channels. Understanding these principles is vital for effective water resource management and engineering applications.
Impartiality as per ISO /IEC 17025:2017 Standard
This document provides basic guidelines for imparitallity requirement of ISO 17025. It defines in detial how it is met and wiudhwdih jdhsjdhwudjwkdbjwkdddddddddddkkkkkkkkkkkkkkkkkkkkkkkwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwioiiiiiiiiiiiii uwwwwwwwwwwwwwwwwhe wiqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq gbbbbbbbbbbbbb owdjjjjjjjjjjjjjjjjjjjj widhi owqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq uwdhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhwqiiiiiiiiiiiiiiiiiiiiiiiiiiiiw0pooooojjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj whhhhhhhhhhh wheeeeeeee wihieiiiiii wihe
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Call Girls Chennai +91-8824825030 Vip Call Girls Chennai
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一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理
原版一模一样【微信：741003700 】【(uofo毕业证书)美国俄勒冈大学毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
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mHealth Israel_Connecting time-dots for Outcomes Prediction in Healthcare Big Data_Robert Moskovitch, PhD, Ben Gurion University of the Negev
- 1. Connecting time-dots for Outcomes Prediction in LongitudinalHeterogeneous Multivariate healthcare Big Data mHealth meetup: Health Tech IP & Data Science Robert Moskovitch, PhD Complex Data Analytics Lab Software and Information Systems Engineering Ben Gurion University of the Negev
- 2. Monitoring for Modeling Glucometer Static: Gender, Height, Weight, socio economic status, Blood type,.. Heart beat Movements -> Activities Applications And more .. Inpatient: • Conditions • Lab-tests • Medications • Procedures Outpatientdata: • Medications (continuous) • Procedures • Conditions • Lab tests
- 4. From Time Points to Time Intervals Series
- 5. Time Intervals Related Patterns Discovery – an illustration
- 6. Time Intervals Related Patterns Discovery – an illustration
- 7. Allen’s (1983) Temporal Logic, using Epsilon
- 8. Exploiting the Transitive Property Ø Given three time intervals A, B and C and the relations among A r1 B and B r2 C, the relation A r3 C can be reasoned.
- 9. Time Intervals Related Pattern - TIRP A TIRP is a conjunction of pairwise temporal relations {A o B, A < C, A < D, A < E, B m C, B < D, B < E, C c D, C o E, D m E} A k-sized TIRP includes k(k-1)/2 = (k2-k)/2 temporal relations
- 10. KarmaLego – Definitions 2 Ø Vertical Support(P) is the numberof entities |EP| (e.g., patients), in which TIRP P was discovered atleast once, among the entire mined population |E|. Ver_sup(P)= |EP| / |E| Ø Horizontal Support (P) is the numberof instances hor_sup(P,ei)occurring in each supporting entity. Ø Mean Duration of the n supporting instances of the same k-sized TIRP P within an entity e is defined by: || ),sup(_ )sup(__ || 1 P E i i E ePhor Phormean P ∑= = ( ) n IIMax ePonMeanDurati n i i s ji e k j∑= = − = 1 1,, 1 ),(
- 11. Time Intervals Related Patterns Discovery – an illustration Procedures Conditions Drugs Procedures Conditions Drugs Procedures Conditions Drugs HS = 2 HS = 2 HS = 3 HS = 1 HS = 1 HS = 1
- 12. K=1 K=4 K=3 K=5 K=2 NULL + A + B+ B + A A B C + C+ B+ A + C+ A + C A B B C r1 r1 r2 A B B C r1 r1 r1 A B B C r1 r1 r3 A B B C r1 r8 r7 A B B C r1 r8 r8 + B + A + A + B + C + B + C + C B C A A B r1 r1 r2 r1 r1 r1C B C A A B r1 r1 r3 r1 r1 r1C B C B A B r1 r1 r3 r1 r4 r5C B C C A B r1 r1 r3 r1 r1 r1C B C C A B r1 r1 r3 r1 r2 r8C r5 r4 r1 B C B A B r1 r1 r3 C r3 r5 r2 r2B C r5 r4 r1 B C B A B r1 r1 r3 C r8 r4 r1 r2B B A A r1 A A r5 A B r1 A B r1 A B r7 A C r1 A C r5 A C r7 KarmaLego Fast Time Intervals Mining 73 = 343 -> 3 Moskovitch et al, Outcomes Prediction via Time Intervals Related Patterns, IEEE International Conference on Data Mining (ICDM), 2015
- 13. KarmaLego General Workflow Moskovitch et al, Fast Time Intervals Mining by Exploiting the Transitivity of Temporal Relations, Knowledge and Information Systems, 2015.
- 14. Use of TIRPs from KarmaLego
- 15. Diabetes Temporal Patterns Example 0.26 0.18 0.22 0.28 0.25 0.23 0.33 0.42 0.29
- 16. KarmaLegoSification Ø A major problem in multivariate time series classification is the various types of raw temporal data Ø TIRPs can be useful here as well, as classification features Moskovitch et al, Classification of Multivariate Time Series via TemporalAbstraction and Time-Intervals Mining, Knowledge and Information Systems, 2015
- 17. Unsupervised Discretization: EWD and SAX Ø EWD: the continuous values range is divided into k equal bins (states) Ø Symbolic Aggregate approXimation Based on PAA, Piecewise Aggregate Approximation, A time series segmenting algorithm (Keogh et al.,2003). Ø TD4C Moskovitch et al, Data Mining and Knowledge Discovery, 2015
- 18. TD4C Temporal Discretization for Classification Ø TD4C performs supervised temporal abstraction to increase the expected accuracy. Ø TD4C: search set of cut-offs to abstract later each temporal variable into meaningfully different states for each class. Ø Having different states for each class -> will discover different frequent TIRPs for each class -> expected to increase the accuracy. Moskovitch et al, Classification-driven temporaldiscretization of multivariate time series, Data Mining and Knowledge Discovery,2015
- 19. TD4C Formulation Ø Given C = {c1, c2,.. cn} classes, E entities divided into {E1, E2,.. Ec} sets of entities per class and T = {t1, t2,.. tm} temporal variables, and A – a TD4C abstraction method. Ø The problem is to find the set of cutoffs for each temporal variable ti that increases the difference in the dominant states in each class. Ø Thus, we want to measure the distribution of the states in each class entities, and to measure when these are most different. Ø For that three measure were determined: l Entropy l Cosinus l Kullback-Leibler
- 20. Generalization of Allen’s Temporal Relations Ø KarmaLegoS enables to mine TIRPs with 7 (Allen’s original) or 3 abstract temporal relations and various epsilon values BEFORE
- 22. Datasets Ø ICU Dataset - 645 patients who underwent cardiac surgery at the AMC in Amsterdam (2002-2004). Includes over 12 hours of High and Low frequency. 196 patients were mechanically ventilated for more than 24 hours (70%), and the rest were 449. Ø Diabetes - Contains 2038 diabetic patients data along 5 years (2002-2007) from Israeli HMO, measured monthly HA1c, Glucose, Cholesterol values and medication purchased. 992 males and 1012 females, having a quite balanced (~50%) dataset. Ø Hepatitis – Laboratory measurements of Hepatitis B and C patients, admitted in Japan. Eleven temporal variables, having the top vertical support. 204 Hepatitis B patients and 294 Hepatitis C patients (~60%).
- 23. KarmaLegoS Evaluation Setup Moskovitch and Shahar, Classification of Multivariate Time Series via Temporal Abstraction and Time-Intervals Mining, Knowledge and Information Systems,2015 Class 1 data Class 2 data Class n data KarmaLego KarmaLego KarmaLego U KarmaLego TIRPs TrainingTest Single Entity data Signle KarmaLego Training Matrix (EntitiesTIRPs and labels) Vector of TIRPs Induced Classifier Feature Selection TIRPs TIRPs TIRPs Class
- 24. KarmaLegoS - Parameters Ø To evaluate KarmaLegoS 5 experiments were designed for the various parameters in the KarmaLegoS framework, including: l Abstraction method (KB, EWD, SAX, TD4Cs) l Number of bins (3, 4) l Temporal relations set (3, 7) l TIRP Representation (Binary, HS, MeanD) Ø For that experiments we designed and ran on three real datasets using 10 fold cross validation and RandomForest, compared according to the Accuracy measure.
- 25. Temporal Relations and TIRP representation
- 26. Abstraction Methods vs Bins Number ε=0, 3 temporal relations, MeanD and NoFS
- 27. Thank You! Dr. Robert Moskovitch Head, Complex Data Analytics Lab Software and Information Systems Engineering Ben Gurion University Israel robertmo@bgu.ac.il
- 28. Backup
- 29. KarmaLegoV
- 30. KarmaLegoV
- 31. KarmaLegoV – Search Results