1) Sepsis is a serious medical condition caused by infection that kills over 200,000 people per year in the US, costing $16.7 billion annually.
2) The project aims to use data mining, artificial intelligence and visualization to better predict sepsis early and recommend optimal treatment by analyzing patient vital signs and other medical data.
3) The system would generate alerts when sepsis is likely, and suggest cost-effective tests or treatments based on a partially observable Markov decision process model optimized for long-term outcomes.
Systematic Reviews: Searching for information on adverse effects by Dr. Su Go...Ann-Marie Roche
In this webinar, Dr. Su Golder, an information specialist at the University of York and with 15 years experience with systematic reviews, covered the following:
- Why we should search for information on adverse effects?
- Why information on adverse effects difficult to search for?
- How we currently search for information on adverse effects?
- How we should search for information on adverse effects?
Using Digital Innovation to Establish Authentic Reporter DialogueSophia Ahrel FCIM
Digital solutions that put patients at forefront of safety processes
Capture relevant, essential and complete data at first interaction
Maximise the value of initial contact and reduce low value follow up
Solutions that ensure REMS and RMP commitments are met and are future proofed
We're developing augmented reality software to help clinicians with pre-surgical planning by providing them with patient-specific, high fidelity 3D holograms that have been derived from the same data used to generate conventional CT scans and MRIs.
Systematic Reviews: Searching for information on adverse effects by Dr. Su Go...Ann-Marie Roche
In this webinar, Dr. Su Golder, an information specialist at the University of York and with 15 years experience with systematic reviews, covered the following:
- Why we should search for information on adverse effects?
- Why information on adverse effects difficult to search for?
- How we currently search for information on adverse effects?
- How we should search for information on adverse effects?
Using Digital Innovation to Establish Authentic Reporter DialogueSophia Ahrel FCIM
Digital solutions that put patients at forefront of safety processes
Capture relevant, essential and complete data at first interaction
Maximise the value of initial contact and reduce low value follow up
Solutions that ensure REMS and RMP commitments are met and are future proofed
We're developing augmented reality software to help clinicians with pre-surgical planning by providing them with patient-specific, high fidelity 3D holograms that have been derived from the same data used to generate conventional CT scans and MRIs.
Hirshberg promise of digital technology astra_zenecaThe Promise of Digital Te...Levi Shapiro
Presentation by Boaz Hirshberg, VP, Clinical Development, Cardiovascular, Renal, Metabolic Disease at AstraZeneca
- The Promise of Digital Technology in Drug Development Clinical Trials. Includes the following:
- The vision for patient-centric medical care delivery
- End-to-end patient experience enhanced by digital technologies
- Digital technologies have a potential to transform clinical trial & medical care delivery
- Example: transforming our understanding of Type 2 diabetes with remote patient monitoring
- Frequent sampling demonstrates glucose lowering very soon after first dose, which might be unappreciated in typical trial design
- Multiple data points reduce uncertainty about the glucose outcome and enable future machine learning of unanticipated relationships
- Lessons learned from CGM pilot: data storage, transfer, and analysis
- Defining the clinical science questions to be answered
- Operational considerations for incorporating digital data into clinical development
- Addressing challenges of digital technologies’ disruption
Medical Deep Learning: Clinical, Technical, & Regulatory Challenges and How t...Devon Bernard
Deep Learning is proving to be a powerful tool that can improve healthcare for both patients and care-providers. In this talk I’ll cover an intro to some of the medical problems currently being solved by deep learning, market adoption, healthcare challenges (e.g regulation, data quality, data acquisition), deep learning challenges (e.g. model stability, training/convergence time, scalable training environment), and tips learned by tackling these problems head-on.
This talk was presented Oct 15, 2017 at http://ai.withthebest.com/.
Using alternative scholarly metrics to showcase the impact of your research: ...SC CTSI at USC and CHLA
Date: Feb 7, 2018
Speaker: Caroline Muglia, Co-Associate Dean for Collections and Technical Services; and Head, Resource Sharing and Collection Assessment, USC Libraries
Overview: Scholarship is increasingly being created, disseminated, and measured on digital and social platforms. If Twitter exchanges, Facebook “saves,” and YouTube hits are the new metrics for tracking scholarship, how are we measuring societal and educational impact and outreach? How can researchers display their research impact using social media on promotion and tenure dossiers? This webinar will discuss altmetrics, alternative scholarly metrics that measure the impact and use of scholarship. We will focus on PlumX, the tool used at USC, which combines traditional and new metrics to paint a comprehensive portrait of your scholarly output and its reach in various communities and with different stakeholders.
How ebp enable healthcare professionals to provide informed decision - PubricaPubrica
Regular steps in EBP
Feature of EBP
Necessity of EBP
Quality of the research publication
Advantages & Disadvantages of EBP
Criticisms of EBP
Continue Reading: https://bit.ly/3dOLWqq
For our services: https://pubrica.com/services/physician-writing-services/clinical-literature-review-for-an-evidence-based-medicine/
Why Pubrica:
When you order our services, We promise you the following – Plagiarism free | always on Time | 24*7 customer support | Written to international Standard | Unlimited Revisions support | Medical writing Expert | Publication Support | Biostatistical experts | High-quality Subject Matter Experts.
Contact us:
Web: https://pubrica.com/
Blog: https://pubrica.com/academy/
Email: sales@pubrica.com
WhatsApp : +91 9884350006
United Kingdom: +44- 74248 10299
Genomic investigations often produce more information than is initially expected. Several documents have addressed this issue. While the approaches to the management of incidental findings (IFs) vary, it is usually recommended that the information be disclosed if there is clinical utility and the possibility of prevention or treatment. This leaves unsolved fundamental issues such as the different ways of interpreting clinical utility and countless sources of uncertainty. Guidelines can offer indications but should not be allowed to relieve healthcare professionals of their responsibilities.
Seventh Annual Next Generation Dx SummitJaime Hodges
The Next Generation Dx Summit (www.nextgenerationdx.com), entering its seventh year, brings together more than 800 diagnostics professionals from across the world, providing comprehensive programming and valuable networking opportunities. Spanning from clinical diagnostics to business strategy, this year’s expanded program encompasses predictive cancer biomarkers, companion diagnostics, infectious disease, point-of-care, pharmacy-based diagnostics, cell-free DNA, commercialization, cancer immunotherapy, and reimbursement. With widespread coverage of all the most relevant diagnostics topics, the Next Generation Dx Summit promises to be a must-attend event to hear the latest announcements and developments in this rapidly evolving field.
An awareness session conducted for physicians of the psyhciatry department at KSUMC on Monday 25/11/2019 at King Khalid University Hospital, Riyadh, KSA
How Researchers Can Get Science Done Faster Using an R&D Services MarketplaceSC CTSI at USC and CHLA
Date: Feb 6, 2019
Topic: How Researchers Can Get Science Done Faster Using an R&D Services Marketplace
Speaker: Dr. Zev Wisotsky is a Senior Scientist and R&D Specialist at Science Exchange, where he assists researchers in connecting with the right R&D providers for their experiments and alerts his clients to newly available technologies. Dr. Wisotsky earned his PhD in neuroscience investigating taste detection using fruit fly and mosquito models at UC Riverside. He then completed postdoctoral research at Stanford studying the role of brain regions involved in fear memory and addiction through optogenetic silencing of different brain circuits.
Overview: Science Exchange is an open marketplace for scientific research that breaks down barriers to collaboration and innovation. The platform makes it easy for researchers to access more than 6,000 services from a network of over 2,500 qualified research providers. In this webinar, you will learn how researchers can use Science Exchange to access new technologies, get competitive quotes for specific projects, and order from any service provider under a single, pre-established contract. The presentation will also include examples of successful projects and collaborations, initiated on the Science Exchange platform, that have accelerated breakthrough
eConsent (electronic informed consent) adoption is on the rise!
100% of the Top 10 and 88% of the Top 25 Pharma have implemented eConsent - What's driving their adoption?
Learn more in our new infographic "14 Drivers of eConsent Adoption in Clinical Trials"
Hirshberg promise of digital technology astra_zenecaThe Promise of Digital Te...Levi Shapiro
Presentation by Boaz Hirshberg, VP, Clinical Development, Cardiovascular, Renal, Metabolic Disease at AstraZeneca
- The Promise of Digital Technology in Drug Development Clinical Trials. Includes the following:
- The vision for patient-centric medical care delivery
- End-to-end patient experience enhanced by digital technologies
- Digital technologies have a potential to transform clinical trial & medical care delivery
- Example: transforming our understanding of Type 2 diabetes with remote patient monitoring
- Frequent sampling demonstrates glucose lowering very soon after first dose, which might be unappreciated in typical trial design
- Multiple data points reduce uncertainty about the glucose outcome and enable future machine learning of unanticipated relationships
- Lessons learned from CGM pilot: data storage, transfer, and analysis
- Defining the clinical science questions to be answered
- Operational considerations for incorporating digital data into clinical development
- Addressing challenges of digital technologies’ disruption
Medical Deep Learning: Clinical, Technical, & Regulatory Challenges and How t...Devon Bernard
Deep Learning is proving to be a powerful tool that can improve healthcare for both patients and care-providers. In this talk I’ll cover an intro to some of the medical problems currently being solved by deep learning, market adoption, healthcare challenges (e.g regulation, data quality, data acquisition), deep learning challenges (e.g. model stability, training/convergence time, scalable training environment), and tips learned by tackling these problems head-on.
This talk was presented Oct 15, 2017 at http://ai.withthebest.com/.
Using alternative scholarly metrics to showcase the impact of your research: ...SC CTSI at USC and CHLA
Date: Feb 7, 2018
Speaker: Caroline Muglia, Co-Associate Dean for Collections and Technical Services; and Head, Resource Sharing and Collection Assessment, USC Libraries
Overview: Scholarship is increasingly being created, disseminated, and measured on digital and social platforms. If Twitter exchanges, Facebook “saves,” and YouTube hits are the new metrics for tracking scholarship, how are we measuring societal and educational impact and outreach? How can researchers display their research impact using social media on promotion and tenure dossiers? This webinar will discuss altmetrics, alternative scholarly metrics that measure the impact and use of scholarship. We will focus on PlumX, the tool used at USC, which combines traditional and new metrics to paint a comprehensive portrait of your scholarly output and its reach in various communities and with different stakeholders.
How ebp enable healthcare professionals to provide informed decision - PubricaPubrica
Regular steps in EBP
Feature of EBP
Necessity of EBP
Quality of the research publication
Advantages & Disadvantages of EBP
Criticisms of EBP
Continue Reading: https://bit.ly/3dOLWqq
For our services: https://pubrica.com/services/physician-writing-services/clinical-literature-review-for-an-evidence-based-medicine/
Why Pubrica:
When you order our services, We promise you the following – Plagiarism free | always on Time | 24*7 customer support | Written to international Standard | Unlimited Revisions support | Medical writing Expert | Publication Support | Biostatistical experts | High-quality Subject Matter Experts.
Contact us:
Web: https://pubrica.com/
Blog: https://pubrica.com/academy/
Email: sales@pubrica.com
WhatsApp : +91 9884350006
United Kingdom: +44- 74248 10299
Genomic investigations often produce more information than is initially expected. Several documents have addressed this issue. While the approaches to the management of incidental findings (IFs) vary, it is usually recommended that the information be disclosed if there is clinical utility and the possibility of prevention or treatment. This leaves unsolved fundamental issues such as the different ways of interpreting clinical utility and countless sources of uncertainty. Guidelines can offer indications but should not be allowed to relieve healthcare professionals of their responsibilities.
Seventh Annual Next Generation Dx SummitJaime Hodges
The Next Generation Dx Summit (www.nextgenerationdx.com), entering its seventh year, brings together more than 800 diagnostics professionals from across the world, providing comprehensive programming and valuable networking opportunities. Spanning from clinical diagnostics to business strategy, this year’s expanded program encompasses predictive cancer biomarkers, companion diagnostics, infectious disease, point-of-care, pharmacy-based diagnostics, cell-free DNA, commercialization, cancer immunotherapy, and reimbursement. With widespread coverage of all the most relevant diagnostics topics, the Next Generation Dx Summit promises to be a must-attend event to hear the latest announcements and developments in this rapidly evolving field.
An awareness session conducted for physicians of the psyhciatry department at KSUMC on Monday 25/11/2019 at King Khalid University Hospital, Riyadh, KSA
How Researchers Can Get Science Done Faster Using an R&D Services MarketplaceSC CTSI at USC and CHLA
Date: Feb 6, 2019
Topic: How Researchers Can Get Science Done Faster Using an R&D Services Marketplace
Speaker: Dr. Zev Wisotsky is a Senior Scientist and R&D Specialist at Science Exchange, where he assists researchers in connecting with the right R&D providers for their experiments and alerts his clients to newly available technologies. Dr. Wisotsky earned his PhD in neuroscience investigating taste detection using fruit fly and mosquito models at UC Riverside. He then completed postdoctoral research at Stanford studying the role of brain regions involved in fear memory and addiction through optogenetic silencing of different brain circuits.
Overview: Science Exchange is an open marketplace for scientific research that breaks down barriers to collaboration and innovation. The platform makes it easy for researchers to access more than 6,000 services from a network of over 2,500 qualified research providers. In this webinar, you will learn how researchers can use Science Exchange to access new technologies, get competitive quotes for specific projects, and order from any service provider under a single, pre-established contract. The presentation will also include examples of successful projects and collaborations, initiated on the Science Exchange platform, that have accelerated breakthrough
eConsent (electronic informed consent) adoption is on the rise!
100% of the Top 10 and 88% of the Top 25 Pharma have implemented eConsent - What's driving their adoption?
Learn more in our new infographic "14 Drivers of eConsent Adoption in Clinical Trials"
EDF2014: Paul Groth, Department of Computer Science & The Network Institute, ...European Data Forum
Invited Talk by Paul Groth, Department of Computer Science & The Network Institute, VU University Amsterdam, Netherlands at the European Data Forum 2014, 20 March 2014 in Athens, Greece: Open PHACTS: A Data Platform for Drug Discovery.
Lecture to SIPA students on basics of creating data visualisations in multi-language, very-diverse-datasets developing-world / emerging-economy environments.
Andrew Satz, Co-Founder of MetrixLabs spoke to us about the realities of data science, artificial intelligence and machine learning and how they will affect patient outcomes.
This year's 3rd Annual TCGC: The Clinical Genome Conference, held June 10-12, 2014 in San Francisco, is a three-day event that weaves together the science of sequencing and the business of implementing genomics in the clinic. It uniquely illustrates the mutual influence of those areas and the need to therefore consider the needs, challenges and opportunities of both - from next-generation sequencing and variant interpretation to insurance reimbursement and electronic health records - throughout the entire research process.Learn more at http://www.clinicalgenomeconference.com
In this talk, we present our work on developing large-scale text mining and machine learning tools as well as their uses in real-world applications in PubMed search, biocuration and healthcare (medical image analysis).
Capstone thesis submitted for undergraduate studies on the utility of genomic surveying tools in improving sudden cardiac arrest risk stratification and prediction of sudden cardiac death.
Genomics, Cellular Networks, Preventive Medicine, and SocietyLarry Smarr
09.12.11
Invited Talk
Guest Lecture to UCSD Medical and Pharmaceutical Students
Genetics in Medicine Course
Amphitheater of the Pharmaceutical Sciences Bldg
Title: Genomics, Cellular Networks, Preventive Medicine, and Society
La Jolla, CA
Heart Disease Prediction using Machine Learning Algorithmijtsrd
Nowadays, Heart disease has become dangerous to a human being, it effects very badly to human body. If anyone is suffering from heart disease, then it leads to blood clotting. Heart disease prediction is very difficult task to predict in the field of medical science. Affiliation has predicted that 12 million people fail horrendously every year as a result of heart disease. In this paper, we propose a k Nearest Neighbors Algorithm KNN way to deal with improve the exactness of heart determination. We show that k Nearest Neighbors Algorithm KNN have better accuracy than random forest algorithm for viewing heart disease. The k Nearest Neighbors Algorithm give more precise and exact outcome . We have taken 13 attributes in the dataset and a target attribute, by applying machine learning we achieved 84 accuracy in the heart disease detection. Ravi Kumar Singh | Dr. A Rengarajan "Heart Disease Prediction using Machine Learning Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38358.pdf Paper Url: https://www.ijtsrd.com/computer-science/other/38358/heart-disease-prediction-using-machine-learning-algorithm/ravi-kumar-singh
HEART DISEASES PREDICTION USING MACHINE LEARNING ALGORITHMPoojaSri45
Implemented a machine learning project aimed at predicting heart diseases using various algorithms and techniques. Developed as a part of academic or professional endeavor, the project demonstrates proficiency in data preprocessing, feature selection, model training, and evaluation.
Similar to pptx - Preventing Sepsis: Artificial Intelligence, Knowledge ... (20)
2. NIH Challenge Grant This application addresses broad Challenge Area (10) Information Technology for Processing Health Care Data Topic, 10-LM-102*: Advanced decision support for complex clinical decisions
3. Clinical Problem: sepsis Definition: serious medical condition characterized by a whole-body inflammatory state (called a systemic inflammatory response syndrome or SIRS) and the presence of a known or suspected infection Top 10 causes of death in the US Kills more than 200,000 per year in the US (more than breast & lung cancer combined)
4. Cost of severe sepsis Estimated cases per year in US: 751,000 Estimated cost per case: $22,100 Estimated total cost per year: $16.7 billion Mortality (in this series): 28% Projected increase 1.5% per annum Angus et al. Epidemiology of severe sepsis in the United States: Analysis of incidence, outcome, and associated costs of care. Critical Care Medicine. July, 2001
5. SIRS Temperature < 36° C or > 38° C Heart Rate > 90 bpm Respiratory Rate > 20 breaths/minor PaCO2 < 32 mmHg White Blood Cell Count > 12,000 or < 4,000 cells/mm3; or > 10% bands
14. Our premise Retrospective chart review often yields time frame when one feels early intervention could have changed outcome Clinical “hunch” that something “bad” might happen which demands more attention What if we could predict sepsis before sepsis criteria were met?
16. How do we do this? Data Mining Artificial Intelligence Visualization (computer-human interface)
17. Data! Data! Data! Heartrate ?????? Temperature PaCO2 Respiratory Rate White Blood Cell Count
18. Marriage of computer science & medicine Data mining identify previously undiscovered patterns and correlations Changes in vital signs Rate of change of the vitals signs Perhaps correlations of seemingly unrelated events Recently found that prior to significant hemodynamic compromise, the variation in heart rate actually decreases in mice
19. Marriage of computer science & medicine Decision making Increased monitoring of vitals? More tests? (Which ones?) Antibiotics? Exploratory surgery? None of the above? What drives decisions? Costs, benefits Likelihood of benefits
20. Marriage of computer science & medicine Artificial Intelligence Model knowledge (from data mining) into partially observable Markov decision process (POMDP)
21. Markov Decision Processes Actions have probabilistic effects Treatments sometimes work Testing can have effects The probabilities depend on the patient’s state and the actions Actions have costs The patient’s state has an immediate value Quality of life M = <S, A, Pr, R>, Pr: SxAxS [0,1]
22. Decision-Theoretic Planning “Plans” are policies: Given the patient’s history, the insurance plan (establishes costs) probabilities of effects Optimize long term expected outcomes (That’s a lot of possibilities, even for computers!) (π: S A)
23. Partially Observable MDPs The patient’s state is not fully observable This makes planning harder Put probabilities on unobserved variables Reason over possible states as well as possible futures (π: Histories A) Optimality is no longer feasible Don’t despair! Satisficing policies are possible.
24. AI Summary Use data mining, machine learning to find patterns and predictors Build POMDP model Find policy that considers long-term expected costs Get alerts when sepsis is likely, suggested tests or treatments that are cost- and outcome-effective
50. Using Visualizations To Solve Real-World Problems… Who Where What Evidence Box Original Data When
51. Using Visualizations To Solve Real-World Problems… This group’s attacks are not bounded by geo-locations but instead, religious beliefs. Its attack patterns changed with its developments.
I recently finished reading a wonderful book by Steven Johnson entitled The Ghost Map: The Story of London’s Most Terrifying Epidemic – and How It Changed Science, Cities, and the Modern World. In the summer of 1854 cholera swept through a section of London with unprecedented intensity. At the time, the cause of cholera was unknown and rapidly growing modern cities such as London, with dense populations packed into small areas, were rich breeding grounds for this disease. Most of those who concerned themselves with disease and its cure held tightly to the miasma theory that cholera spread through the air and was associated with the bad smells and the unclean urban environments that produced them. In fact, cholera is a bacterium, which was spreading through the water supply. This book tells the story much as a journalist who witnessed it firsthand would do, but a journalist who had the advantage of hindsight informed by knowledge of modern medicine.Several people of the time play important roles in this story – none more than John Snow, a medical doctor and research scientist. The ghost map refers to a map that he drew by hand during the process of his investigations, which could clearly demonstrate to anyone with open eyes that the source of the outbreak was the Broad Street well. Despite the evidence that this map displayed, however, the miasma theory of cholera transmission prevailed for several years after the epidemic. Eventually, due largely to the tenacious efforts of John Snow and an unlikely supporter, Reverend Henry Whitehead, the evidence won out and steps were taken to eliminate the conditions in which cholera could spread.