Integrated Healthcare Approach to manage multi-morbiditiesPeter Rosengren
The PICASO project will improve cooperation and exchange of knowledge between professional caregivers in health, rehabilitation and social care domains and actively include patients and their relatives in the integrated care settings thus supporting patient empowerment and self-care (the safe hand-off).
The project implements blockchain technology to support distributed electronic patient records and cloud service orchestration to support an holistic and integrated care approach
Integrated Healthcare Approach to manage multi-morbiditiesPeter Rosengren
The PICASO project will improve cooperation and exchange of knowledge between professional caregivers in health, rehabilitation and social care domains and actively include patients and their relatives in the integrated care settings thus supporting patient empowerment and self-care (the safe hand-off).
The project implements blockchain technology to support distributed electronic patient records and cloud service orchestration to support an holistic and integrated care approach
"Performance Analysis of In-Network Caching in Content-Centric Advanced Meter...Khaled Ben Driss
"Performance Analysis of In-Network Caching in Content-Centric Advanced Metering Infrastructure" The International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 11, 2016.
How to run the blockchain.info Bitcoin wallet in NodeJS (experimental).
Dutch Blockchain Hackathon - Tech Deep Dive - 2016-12-07 in Delft
Presentation made with Deckset, source:
https://gist.github.com/Sjors/b39f1e4135c05e8dfe2cf337608ec7a8
Instructions:
https://github.com/blockchain/My-Wallet-V3/wiki/NodeJS
How to create a Dapp - In this presentation I explain some Ethereum concepts to understand Dapps - and put this into practice using a real example : Allowance : A smart contract driven Dapp that allows a parent to give a weekly allowance to his/her kids. It was presented om aug 10 2016 in Antwerp in the API Craftsmanship Belgium meetup. Enjoy
AdsCash Coin: Ethereum Smart Contract based Cryptocurrency for AdWorldNigel Mark Dias
AdsCash is a multifunctional, next-generation cryptocurrency and trading
platform developed on Ethereum blockchain, using cutting edge smart contract
technology. AdsCash is a decentralized peer-to- peer cryptocurrency with a
primary focus on transparency , compliance and security. AdsCash will become the
first stable digital currency exclusively designed and marketed towards the
advertising industry to allow owners of the currency to pay for product and
services with zero chargebacks and freedom from dealing traditional financial
institutions.
Anomaly Detection and Spark Implementation - Meetup Presentation.pptxImpetus Technologies
StreamAnalytix sponsored a meetup on “Anomaly Detection Techniques and Implementation using Apache Spark” which took place on Tuesday December 5, 2017 at Larkspur Landing Milpitas Hotel, Milpitas, CA. The meetup was led by Maxim Shkarayev, Lead Data Scientist, Impetus Technologies along with Punit Shah, Solution Architect, StreamAnalytix and Anand Venugopal, Product Head & AVP, StreamAnalytix, who introduced and summarized the vast field of Anomaly Detection and its applications in various industry problems. The speakers at the event also offered a structured approach to choose the right anomaly detection techniques based on specific use-cases and data characteristics which was followed by a demonstration of some real-world anomaly detection use-cases on Apache Spark based analytics platform.
"Performance Analysis of In-Network Caching in Content-Centric Advanced Meter...Khaled Ben Driss
"Performance Analysis of In-Network Caching in Content-Centric Advanced Metering Infrastructure" The International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 11, 2016.
How to run the blockchain.info Bitcoin wallet in NodeJS (experimental).
Dutch Blockchain Hackathon - Tech Deep Dive - 2016-12-07 in Delft
Presentation made with Deckset, source:
https://gist.github.com/Sjors/b39f1e4135c05e8dfe2cf337608ec7a8
Instructions:
https://github.com/blockchain/My-Wallet-V3/wiki/NodeJS
How to create a Dapp - In this presentation I explain some Ethereum concepts to understand Dapps - and put this into practice using a real example : Allowance : A smart contract driven Dapp that allows a parent to give a weekly allowance to his/her kids. It was presented om aug 10 2016 in Antwerp in the API Craftsmanship Belgium meetup. Enjoy
AdsCash Coin: Ethereum Smart Contract based Cryptocurrency for AdWorldNigel Mark Dias
AdsCash is a multifunctional, next-generation cryptocurrency and trading
platform developed on Ethereum blockchain, using cutting edge smart contract
technology. AdsCash is a decentralized peer-to- peer cryptocurrency with a
primary focus on transparency , compliance and security. AdsCash will become the
first stable digital currency exclusively designed and marketed towards the
advertising industry to allow owners of the currency to pay for product and
services with zero chargebacks and freedom from dealing traditional financial
institutions.
Anomaly Detection and Spark Implementation - Meetup Presentation.pptxImpetus Technologies
StreamAnalytix sponsored a meetup on “Anomaly Detection Techniques and Implementation using Apache Spark” which took place on Tuesday December 5, 2017 at Larkspur Landing Milpitas Hotel, Milpitas, CA. The meetup was led by Maxim Shkarayev, Lead Data Scientist, Impetus Technologies along with Punit Shah, Solution Architect, StreamAnalytix and Anand Venugopal, Product Head & AVP, StreamAnalytix, who introduced and summarized the vast field of Anomaly Detection and its applications in various industry problems. The speakers at the event also offered a structured approach to choose the right anomaly detection techniques based on specific use-cases and data characteristics which was followed by a demonstration of some real-world anomaly detection use-cases on Apache Spark based analytics platform.
Anomaly Detection - Real World Scenarios, Approaches and Live ImplementationImpetus Technologies
Detecting anomalous patterns in data can lead to significant actionable insights in a wide variety of application domains, such as fraud detection, network traffic management, predictive healthcare, energy monitoring and many more.
However, detecting anomalies accurately can be difficult. What qualifies as an anomaly is continuously changing and anomalous patterns are unexpected. An effective anomaly detection system needs to continuously self-learn without relying on pre-programmed thresholds.
Join our speakers Ravishankar Rao Vallabhajosyula, Senior Data Scientist, Impetus Technologies and Saurabh Dutta, Technical Product Manager - StreamAnalytix, in a discussion on:
Importance of anomaly detection in enterprise data, types of anomalies, and challenges
Prominent real-time application areas
Approaches, techniques and algorithms for anomaly detection
Sample use-case implementation on the StreamAnalytix platform
R.G. (Randy) Goebel is currently professor of Computing Science in the Department of Computing Science at the University of Alberta, Associate Vice President (Research) and Associate Vice President (Academic), and founding principle investigator in the Alberta Machine Intelligence Institute (AMII).
He received the B.Sc. (Computer Science), M.Sc. (Computing Science), and Ph.D. (Computer Science) from the Universities of Regina, Alberta, and British Columbia, respectively.
Professor Goebel's theoretical work on abduction, hypothetical reasoning and belief revision is internationally well know, and his recent research is focused on the formalization of visualization and explainable artificial intelligence (XAI).
He has worked on optimization, algorithm complexity, systems biology, and natural language processing, including applications in legal reasoning and medical informatics.
Randy has previously held faculty appointments at the University of Waterloo, University of Tokyo, Multimedia University (Kuala Lumpur), Hokkaido University (Sapporo), visiting researcher engagements at National Institute of Informatics (Tokyo), DFKI (Germany), and NICTA (now Data61, Australia); is actively involved in collaborative research projects in Canada, Japan, China, and Germany.
KeyAI. Solving a math problem to recover lost crypto assets.RFID INC
KeyAI: Restoring Access, Recovering Value. We are a startup in the field of cryptography and artificial intelligence, aiming to develop an algorithm capable of predicting private keys from public ones using deep learning. Our value proposition is the ability to recover access to crypto assets lost due to forgotten or misplaced keys, which, according to our estimates, accounts for about 20% of all cryptocurrencies as of 2023. KeyAI offers an advanced AI model for predicting private keys, thereby restoring access to valuable cryptocurrency assets. Our business model involves charging users a fee as a percentage of the value of the restored assets, varying depending on the size of the assets and the complexity of key recovery.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
3. Problem to solve?
Bitcoin keep money honest proof of work
Ethereum keep contracts honest proof work gas
Maidsafe keep data honest proof of resource
Health ?
– keep science honest proof of evidence
5. Pull Personalised Health
Health of Environment
Well being --- Lifestyle --- Healthy aging
Prevention - Repair – Evidence based
Social Activities Food
Peernetworkvalidateshealthclaims&selfregulates
Living Scientific Knowledge Network
Sensors Genetics DIY
Rea time validation Self regulating
Algorithms
Genetics Attention – Interaction - Action
6. Pull Precision Medicine
Health of Environment
Well being --- Lifestyle --- Healthy aging
Precision Medicine – Evidence based
Mental Medicine Palliative care
Basic Scientific Knowledge
Diagnostic Equip. Drugs Surgery
Clinical trials Regulations
Algorithms
'Peer' review
Genetics Attention – Interaction - Action
8. Xray Workflow
Identity
ML Compute
Sensors - xray
Storage API
Regulation
Compliance
Permissions
Individual
Clinician
Radiog.
ID A
Clin Dr. B
Rad. C
Comp. ML1
Maidsafe
Evidence Chain
Decision
Protocol
Actionxray
9. Early community efforts
Estonia Health Records
White papers clinical trails reproducible science
Government Funding Research
Startups - GEM
Corporate – Philips Blockchain LAB
Code - github
14. ZKP
• Zero-knowledge proof (discrete logs). ZKP. Outlines zero-knowledge proof.
• Zero-knowledge proof (Feige-Fiat-Shamir). ZKP. Outlines zero-knowledge proof
using the Feige-Fiat-Shamir method.
• Zero-knowledge proof (non-interactive random oracle access). ZKP. Non-
interactive random oracle access for the Fiat-Shamir heuristic.
• Zero-knowledge proof (Graphs). ZKP. Outlines zero-knowledge proof using
graphing methods.
• Fair coin flip. ZKP. Outlines how a fair coin flip can be created, without a trusted
verifier.
• Voting with Paillier crypto system. ZKP. Outlines voting with Paillier crypto
system.
• Oblivious transfer. OT. Oblivious transfer.
• Scrambled circuits. Scrambled. Scrambled circuits - SFE.
• Millionaire's Problem . Mill. Yao's Millionaire Problem.
• RAPPOR. RAPPOR. Outlines RAPPOR (Randomized Aggregatable Privacy-
Preserving. Ordinal Response) which allows for privacy in gathered data.
15. Quantum Robust
• Lattice-based cryptography [Lattice] – This classification shows great
potential and is leading to new cryptography, such as for fully
homomorphic encryption [here], and code obfuscation. An example is
given in the following section.
• Code-based cryptography [McEliece] – This method was created in 1978
with the McEliece cryptosystem but has barely been using in real
applications. The McEliece method uses linear codes that are used in
error correcting codes, and involves matrix-vector multiplication. An
example of a linear code is Hamming code [here].
• Multivariate polynomial cryptography [UOV] – These focus on the
difficulty of solving systems of multivariate polynomials over finite
fields. Unfortunately, many of the methods that have been proposed
have already been broken.
• Hash-based signatures [GMSS] – This would involve created digital
signatures using hashing methods. The drawback is that a signer needs
to keep a track of all of the messages that have been signed, and that
there is a limit to the number of signatures that can be produced.