Presentation by Prof. Fernando Martin-Sanchez at the "Carlton Connect" Interdisciplinary conference in Melbourne, 2012.
http://www.carltonconnect.com.au/Conference/Conference.html
This document discusses how broadband technologies can enable personalized and participatory medicine. It describes how broadband can help improve youth mental health services and aged care through remote monitoring, telehealth, and electronic health records. The convergence of medicine and digital technologies is creating an information ecosystem that will facilitate more efficient preventative, diagnostic and therapeutic solutions where citizens have access to their genetic and health data. High-capacity broadband networks that transmit large volumes of data will be important for concepts like personalized medicine and participatory health to become feasible.
Using Mobile Technologies in Health Research at NIHyan_stanford
The document discusses mHealth and the NIH's role in supporting related research. It defines mHealth as using mobile technologies like phones and sensors to improve healthcare. The NIH funds mHealth through grants and initiatives. Challenges include the fast pace of tech versus slow funding cycles. The NIH hosts workshops and trainings to foster collaboration and develop evidence-based mHealth research.
Health and Biomedical informatics aims to use information processing for preventative medicine. The presentation outlines current challenges in medicine including the need for earlier diagnosis, personalized therapies, and improved disease classification. It presents a vision called "Health by Equation" which uses an informatics system to calculate an individual's health profile based on genetic and environmental factors to guide prevention and treatment recommendations. Opportunities from health informatics and technology include measuring an individual's genome, phenome, and exposome over lifetime through various sensors. This enables concepts like personalized medicine, participatory health through social media, and crowdsourced clinical trials.
This document discusses the opportunity for transformation in healthcare through a P4 (Predictive, Preventive, Personalized, and Participatory) approach. It notes that the current healthcare system spends most of its resources on treating preventable chronic diseases. It proposes using complex systems approaches and personalized medicine to shift focus toward prevention, wellness, and patient engagement. The document outlines pilot projects at Ohio State applying a P4 approach to wellness and care coordination for chronic conditions.
The document discusses the transition from personalized medicine to personal health. It notes the current challenges in medicine including the need for earlier diagnosis, more personalized therapies, and improved disease classification. Personalized medicine uses an individual's genetic and molecular profile to guide risk assessment and treatment. However, personal health empowers patients by providing them access to their own health data through technologies like sensors, apps, and personal health records. This allows patients to better monitor and manage their health. Realizing personal health will require overcoming challenges regarding privacy, security, and ensuring equitable access to technologies and data interpretation.
Computing for Human Experience: Semantics empowered Cyber-Physical, Social an...Amit Sheth
Keynote at On the Move conference, October 2011, Greece.
Abstract:
Traditionally, we had to artificially simplify the complexity and richness of the real world to constrained computer models and languages for more efficient computation. Today, devices, sensors, human-in-the-loop participation and social interactions enable something more than a “human instructs machine” paradigm. Web as a system for information sharing is being replaced by pervasive computing with mobile, social, sensor and devices dominated interactions. Correspondingly, computing is moving from targeted tasks focused on improving efficiency and productivity to a vastly richer context that support events and situational awareness, and enrich human experiences encompassing recognition of rich sets of relationships, events and situational awareness with spatio-temporal-thematic elements, and socio-cultural-behavioral facets. Such progress positions us for what I call an emerging era of “computing for human experience” (CHE). Four of the key enablers of CHE are: (a) bridging the physical/digital (cyber) divide, (b) elevating levels of abstractions and utilizing vast background knowledge to enable integration of machine and human perception, (c) convert raw data and observations, ranging from sensors to social media, into understanding of events and situations that are meaningful to humans, and (d) doing all of the above at massive scale covering the Web and pervasive computing supported humanity. Semantic Web (conceptual models/ontologies and background knowledge, annotations, and reasoning) techniques and technologies play a central role in important tasks such as building context, integrating online and offline interactions, and help enhance human experience in their natural environment.
In this talk I will discuss early enablers of CHE including semantics-empowered social networking and sensor Web, and computation of higher level abstractions from raw and phenomenological data. An article in IEEE Internet Computing provides background information: http://bit.ly/HumanExperience
Keynote at: https://www.springer.com/us/book/9783642251054
Event Date: Oct 18, 2011
The document discusses a conference on the role of telehealth in managing rural neuroemergencies. It provides context on the healthcare environment including reforms, technology advances, and challenges in access to care. Telehealth and health information technology are presented as part of the solution to close gaps in rural healthcare access through clinical consultations, education, and health information exchange. Examples of telehealth applications described include telestroke assessments, maternal-fetal medicine, teleradiology, and remote patient monitoring.
This document discusses how broadband technologies can enable personalized and participatory medicine. It describes how broadband can help improve youth mental health services and aged care through remote monitoring, telehealth, and electronic health records. The convergence of medicine and digital technologies is creating an information ecosystem that will facilitate more efficient preventative, diagnostic and therapeutic solutions where citizens have access to their genetic and health data. High-capacity broadband networks that transmit large volumes of data will be important for concepts like personalized medicine and participatory health to become feasible.
Using Mobile Technologies in Health Research at NIHyan_stanford
The document discusses mHealth and the NIH's role in supporting related research. It defines mHealth as using mobile technologies like phones and sensors to improve healthcare. The NIH funds mHealth through grants and initiatives. Challenges include the fast pace of tech versus slow funding cycles. The NIH hosts workshops and trainings to foster collaboration and develop evidence-based mHealth research.
Health and Biomedical informatics aims to use information processing for preventative medicine. The presentation outlines current challenges in medicine including the need for earlier diagnosis, personalized therapies, and improved disease classification. It presents a vision called "Health by Equation" which uses an informatics system to calculate an individual's health profile based on genetic and environmental factors to guide prevention and treatment recommendations. Opportunities from health informatics and technology include measuring an individual's genome, phenome, and exposome over lifetime through various sensors. This enables concepts like personalized medicine, participatory health through social media, and crowdsourced clinical trials.
This document discusses the opportunity for transformation in healthcare through a P4 (Predictive, Preventive, Personalized, and Participatory) approach. It notes that the current healthcare system spends most of its resources on treating preventable chronic diseases. It proposes using complex systems approaches and personalized medicine to shift focus toward prevention, wellness, and patient engagement. The document outlines pilot projects at Ohio State applying a P4 approach to wellness and care coordination for chronic conditions.
The document discusses the transition from personalized medicine to personal health. It notes the current challenges in medicine including the need for earlier diagnosis, more personalized therapies, and improved disease classification. Personalized medicine uses an individual's genetic and molecular profile to guide risk assessment and treatment. However, personal health empowers patients by providing them access to their own health data through technologies like sensors, apps, and personal health records. This allows patients to better monitor and manage their health. Realizing personal health will require overcoming challenges regarding privacy, security, and ensuring equitable access to technologies and data interpretation.
Computing for Human Experience: Semantics empowered Cyber-Physical, Social an...Amit Sheth
Keynote at On the Move conference, October 2011, Greece.
Abstract:
Traditionally, we had to artificially simplify the complexity and richness of the real world to constrained computer models and languages for more efficient computation. Today, devices, sensors, human-in-the-loop participation and social interactions enable something more than a “human instructs machine” paradigm. Web as a system for information sharing is being replaced by pervasive computing with mobile, social, sensor and devices dominated interactions. Correspondingly, computing is moving from targeted tasks focused on improving efficiency and productivity to a vastly richer context that support events and situational awareness, and enrich human experiences encompassing recognition of rich sets of relationships, events and situational awareness with spatio-temporal-thematic elements, and socio-cultural-behavioral facets. Such progress positions us for what I call an emerging era of “computing for human experience” (CHE). Four of the key enablers of CHE are: (a) bridging the physical/digital (cyber) divide, (b) elevating levels of abstractions and utilizing vast background knowledge to enable integration of machine and human perception, (c) convert raw data and observations, ranging from sensors to social media, into understanding of events and situations that are meaningful to humans, and (d) doing all of the above at massive scale covering the Web and pervasive computing supported humanity. Semantic Web (conceptual models/ontologies and background knowledge, annotations, and reasoning) techniques and technologies play a central role in important tasks such as building context, integrating online and offline interactions, and help enhance human experience in their natural environment.
In this talk I will discuss early enablers of CHE including semantics-empowered social networking and sensor Web, and computation of higher level abstractions from raw and phenomenological data. An article in IEEE Internet Computing provides background information: http://bit.ly/HumanExperience
Keynote at: https://www.springer.com/us/book/9783642251054
Event Date: Oct 18, 2011
The document discusses a conference on the role of telehealth in managing rural neuroemergencies. It provides context on the healthcare environment including reforms, technology advances, and challenges in access to care. Telehealth and health information technology are presented as part of the solution to close gaps in rural healthcare access through clinical consultations, education, and health information exchange. Examples of telehealth applications described include telestroke assessments, maternal-fetal medicine, teleradiology, and remote patient monitoring.
Updates on the BioSense Program Redesign: 2011 Public Health Preparedness SummitTaha Kass-Hout, MD, MS
Most state and local health departments are involved in on-going traditional disease surveillance and are beginning to access information through health information exchange with clinical partners. Biosurveillance initiatives offer the opportunity to leverage these existing initiatives while providing important data to protect community health. Building on these existing activities and relationships is key to the success of national initiatives such as BioSense Redesign and meaningful use of electronic health records as a component of the evolving nationwide health information network (NHIN). During this session/workshop, the National Association of County and City Health Officials (NACCHO) and the Association of State and Territorial Health Officials (ASTHO) in association with the Centers for Disease Control and Prevention will address discuss the BioSense redesign effort and provide opportunities for extended engagement of local and state health officials. This workshop encourages the participation of public health emergency responders, and local public health personnel involved in bio-surveillance for emergency preparedness and response within their jurisdictions.
Update to the International Meeting on Emerging Diseases and Surveillance (IMED) community on the latest activities for the BioSense Program redesign and public health syndromic surveillance (PHSS) meaningful use objective.
Orange Healthcare provides communication solutions to help modernize healthcare infrastructure and connect medical professionals and patients. Personalized medicine is evolving from a focus on cancer to utilizing new technologies like big data, enabling access to information, and remote monitoring. In the future, DNA sequencing will cost $100, predictive medicine will be available for everyone, and patients will generate their own health data through mobile devices and the medical cloud. However, personalized medicine will require moving past the myths of the omniscient physician and patient-led healthcare revolution, and ensuring healthcare professionals can properly monitor and interpret the large amounts of data being collected.
CHIC is a nonprofit collaborative in Northeastern Minnesota that provides regional access to health care information through technology and partnerships. Its mission is to help members improve care and save costs. CHIC programs include emergency preparedness coordination, a health information exchange called HIE-Bridge that allows quick access to patient records, an immunization registry, and helping providers apply for telehealth funding. CHIC aims to build bridges to quality health care through these collaborative programs.
The information technology played an important role in information
and knowledge dissemination in the last decade. The usage of IT to
transfer information and knowledge in the animal health care domain
using expert systems is one of the areas investigated by many
institutions. The current era is witnessing a vast development in all
fields of animal health care. Therefore there is a need for an
unconventional method to transfer the knowledge of experts in this
domain to the general public of livestock holders, especially that the
number of experts in new technologies is lesser than their demand in a
certain domain. The transfer of knowledge from veterinary consultants
& scientists to livestock holders represents a bottleneck for the
development of animal health care in any country. Expert systems are
simply computer software programs that mimic the behaviour of human
experts. They are one of the successful applications of the Artificial
Intelligence field, a branch in Computer Science that investigates how
to make the machine think like human or do tasks that humans do.
Expert Systems are very helpful to ensure an effective and nationally
coordinated approach in response to emergency incidents and in routine
bio-security activities. Such systems enable better management of the
information and resources used to manage animal’s diseases and
emergency responses to incursions.
The Role of Information Communication Technology & Geoinformatics in Vector C...ANUMBA JOSEPH UCHE
Driving forces behind a growing interest in Integrated Vector Management include the need to overcome challenges experienced with conventional single-intervention approaches to vector control as well as recent opportunities for promoting multi-sectoral approaches to human health.
In any vector based disease, the most important process in controlling it is monitoring the vector population (Surveillance). This surveillance is important to prioritize the area for treatment and vector control measures.
By providing the tools (ICT & Geoinformatics) to better understand surveillance results, Integrated Vector Management Officers across Nigeria can optimize their own surveillance programs.
Extension personnel can use the system for educating the public and potentially save human lives.
Hence, the integration of ICT & Geoinformatics in vector surveillance ought to be a fundamental skill for modern Integrated Vector Management officers across the Globe
The document summarizes the development of ubiquitous healthcare (U-Healthcare) and a proposed elderly-friendly healthcare smart home system in Korea. It discusses the origins of concepts like house calls, telemedicine, and how U-Healthcare expanded medical services anywhere and anytime. It then describes a proposed smart home model that provides integrated health management for elderly residents through online and offline services linked across living spaces, community spaces, and medical facilities. The model aims to develop a low-cost system centered around residents' needs rather than diseases alone. Ideas are generated using design thinking methods and an example clinical decision support system is presented using various health sensors and feedback.
Piemonte healthcare initiatives aim to address rising costs and citizen expectations through ICT projects. Projects focus on chronic diseases, predictive medicine, and assistive technologies for aging populations. ICT supports a shift from curative to preventive care and from hospital-based to patient-centered care. This includes home monitoring, tele-rehabilitation, lifestyle monitoring, and assistive robots. The overall goal is a sustainable healthcare system through ICT-enabled collaborative and personalized care.
The document discusses giving patients more control over their health records by allowing them access to their full electronic health records. It argues that patients are in the best position to coordinate their care across different specialists and institutions, as they are the only common party that interacts with all caregivers. The document also presents some case studies of organizations that have successfully implemented more patient-controlled personal health records, including Great Ormond Street Hospital, UCL Hospital, and Novartis. It envisions a future where patients can take a more active role in managing their health data and sharing information with clinicians.
Data Analytics Project proposal: Smart home based ambient assisted living - D...Tarun Swarup
In Ambient Assisted Living environments, monitoring the elderly population can detect a wide range of environmental and user-specific parameters such as daily activities, a regular period of inactivity, usual behavioural patterns and other basic routines. The prime goal of this proposal is to experiment the anomaly detection methods and clustering techniques such as K-means, local outlier factor, K-nearest, DBSCAN and CURE on data and determine the most efficient and accurate method among all.
Mike Jackson, Chairman of Shaping Tomorrow, presented on the future of healthcare. Key points include:
1) Healthcare systems have lagged 10 years in translating clinical research into practice, neglecting major health issues. Continuous scanning is needed to enable preventative and predictive care.
2) Future healthcare will be predictive, preventative, precise, participatory and personalized through technologies like genomics, digital implants, and mobile health monitoring.
3) By 2025, patients will be at the center of their own care, aided by new technologies, while universal genetics and regenerative medicine become standard. Healthcare will increasingly shift to the home instead of institutions.
mHealth Israel_Dr. Marvin Slepian_ Innovation: A Vital Ingredient for the Ad...Levi Shapiro
To remain as an effective leading force in the US, world-wide and society in general, Medicine has to actively adopt Innovation in its teaching and culture, rather than letting it occur passively. Dr. Slepian discusses Innovation Thinking and Science for addressing the enormous healthcare challenges facing the US.
Innovation is needed to overcome the many stresses that exist
on Medicine today - increased prevention, better Dxics and Txics
cost-effectiveness, increased access to care
1. Multiple sclerosis (MS) is a chronic disease of the central nervous system affecting young adults that causes progressive motor and cognitive deterioration.
2. The pathogenesis of MS is not fully understood but is thought to involve an interaction of environmental, epigenetic, and genetic factors triggering the disease in susceptible individuals.
3. Efforts are focusing on identifying biomarkers that can optimize disease management and improve prognosis.
Design of a Clinical Decision Support System Framework for the Diagnosis and ...Editor IJCATR
This paper proposes an adaptive framework for a Knowledge Based Intelligent Clinical Decision Support System for the
prediction of hepatitis B which is one of the most deadly viral infections that has a monumental effect on the health of people afflicted
with it and has for long remained a perennial health problem affecting a significant number of people the world over. In the framework
the patient information is fed into the system; the Knowledge base stores all the information to be used by the Clinical Decision
Support System and the classification/prediction algorithm chosen after a thorough evaluation of relevant classification algorithms for
this work is the C4.5 Decision Tree Algorithm with its percentage of correctly classified instances given as 61.0734%; it searches the
Knowledge base recursively and matches the patient information with the pertinent rules that suit each case and thereafter gives the
most precise prediction as to whether the patient is prone to hepatitis B or not. This approach to the prediction of hepatitis B provides a
very potent solution to the problem of determining if a person has the likelihood of developing this dreaded illness or is almost not
susceptible to the ailment.
The Saudi Human Genome Program (SHGP) aims to sequence 100,000 human genomes over five years to study genetic diseases in Saudi Arabia. Genetic diseases have a high burden in Saudi Arabia due to high rates of marriage between relatives. The SHGP was established to identify disease-causing genes and variants specific to the Saudi population using next-generation sequencing across genome centers. It has sequenced over 5,000 samples so far and aims to establish a genomic knowledge database to enable personalized medicine and screening efforts in Saudi Arabia.
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"CTSI at UCSF
Keith R. Yamamoto, PhD — Opening Remarks – Precision Medicine
Vice Chancellor for Research
Executive Vice Dean of the School of Medicine
Professor of Cellular and Molecular Pharmacology
UCSF
1) The document discusses the Future Health department at KU Leuven which conducts research in health decision support for professionals, patients, and policymakers.
2) The department takes an interdisciplinary approach and focuses on using data mining, IT, and software design to extract appropriate information from clinical, biomedical, and other health data sources to provide decision support.
3) The goal is to enable better, more cost effective healthcare by providing personalized decision support that is evidence-based, user-centered, and looks ahead to future needs.
The rise of the 'ePatient': how it is affecting clinical practice and research
The document discusses how engaged patients, or "ePatients", who actively gather their own health data and conduct their own research are affecting clinical practice and research. It describes how ePatients are empowered through personal health records, diagnostic testing, genomic data, and self-monitoring devices. This shift towards participatory health challenges traditional clinician-led models and will require changes in areas like privacy, education, and how data is integrated into care.
Presentation given by Prof Fernando J Martin-Sanchez at the HISA (Health Informatics Society Australia) event "A Leap into E-Health" - see http://www.hisa.org.au/events/event_details.asp?id=211738 for further details - on 29th February 2012.
Updates on the BioSense Program Redesign: 2011 Public Health Preparedness SummitTaha Kass-Hout, MD, MS
Most state and local health departments are involved in on-going traditional disease surveillance and are beginning to access information through health information exchange with clinical partners. Biosurveillance initiatives offer the opportunity to leverage these existing initiatives while providing important data to protect community health. Building on these existing activities and relationships is key to the success of national initiatives such as BioSense Redesign and meaningful use of electronic health records as a component of the evolving nationwide health information network (NHIN). During this session/workshop, the National Association of County and City Health Officials (NACCHO) and the Association of State and Territorial Health Officials (ASTHO) in association with the Centers for Disease Control and Prevention will address discuss the BioSense redesign effort and provide opportunities for extended engagement of local and state health officials. This workshop encourages the participation of public health emergency responders, and local public health personnel involved in bio-surveillance for emergency preparedness and response within their jurisdictions.
Update to the International Meeting on Emerging Diseases and Surveillance (IMED) community on the latest activities for the BioSense Program redesign and public health syndromic surveillance (PHSS) meaningful use objective.
Orange Healthcare provides communication solutions to help modernize healthcare infrastructure and connect medical professionals and patients. Personalized medicine is evolving from a focus on cancer to utilizing new technologies like big data, enabling access to information, and remote monitoring. In the future, DNA sequencing will cost $100, predictive medicine will be available for everyone, and patients will generate their own health data through mobile devices and the medical cloud. However, personalized medicine will require moving past the myths of the omniscient physician and patient-led healthcare revolution, and ensuring healthcare professionals can properly monitor and interpret the large amounts of data being collected.
CHIC is a nonprofit collaborative in Northeastern Minnesota that provides regional access to health care information through technology and partnerships. Its mission is to help members improve care and save costs. CHIC programs include emergency preparedness coordination, a health information exchange called HIE-Bridge that allows quick access to patient records, an immunization registry, and helping providers apply for telehealth funding. CHIC aims to build bridges to quality health care through these collaborative programs.
The information technology played an important role in information
and knowledge dissemination in the last decade. The usage of IT to
transfer information and knowledge in the animal health care domain
using expert systems is one of the areas investigated by many
institutions. The current era is witnessing a vast development in all
fields of animal health care. Therefore there is a need for an
unconventional method to transfer the knowledge of experts in this
domain to the general public of livestock holders, especially that the
number of experts in new technologies is lesser than their demand in a
certain domain. The transfer of knowledge from veterinary consultants
& scientists to livestock holders represents a bottleneck for the
development of animal health care in any country. Expert systems are
simply computer software programs that mimic the behaviour of human
experts. They are one of the successful applications of the Artificial
Intelligence field, a branch in Computer Science that investigates how
to make the machine think like human or do tasks that humans do.
Expert Systems are very helpful to ensure an effective and nationally
coordinated approach in response to emergency incidents and in routine
bio-security activities. Such systems enable better management of the
information and resources used to manage animal’s diseases and
emergency responses to incursions.
The Role of Information Communication Technology & Geoinformatics in Vector C...ANUMBA JOSEPH UCHE
Driving forces behind a growing interest in Integrated Vector Management include the need to overcome challenges experienced with conventional single-intervention approaches to vector control as well as recent opportunities for promoting multi-sectoral approaches to human health.
In any vector based disease, the most important process in controlling it is monitoring the vector population (Surveillance). This surveillance is important to prioritize the area for treatment and vector control measures.
By providing the tools (ICT & Geoinformatics) to better understand surveillance results, Integrated Vector Management Officers across Nigeria can optimize their own surveillance programs.
Extension personnel can use the system for educating the public and potentially save human lives.
Hence, the integration of ICT & Geoinformatics in vector surveillance ought to be a fundamental skill for modern Integrated Vector Management officers across the Globe
The document summarizes the development of ubiquitous healthcare (U-Healthcare) and a proposed elderly-friendly healthcare smart home system in Korea. It discusses the origins of concepts like house calls, telemedicine, and how U-Healthcare expanded medical services anywhere and anytime. It then describes a proposed smart home model that provides integrated health management for elderly residents through online and offline services linked across living spaces, community spaces, and medical facilities. The model aims to develop a low-cost system centered around residents' needs rather than diseases alone. Ideas are generated using design thinking methods and an example clinical decision support system is presented using various health sensors and feedback.
Piemonte healthcare initiatives aim to address rising costs and citizen expectations through ICT projects. Projects focus on chronic diseases, predictive medicine, and assistive technologies for aging populations. ICT supports a shift from curative to preventive care and from hospital-based to patient-centered care. This includes home monitoring, tele-rehabilitation, lifestyle monitoring, and assistive robots. The overall goal is a sustainable healthcare system through ICT-enabled collaborative and personalized care.
The document discusses giving patients more control over their health records by allowing them access to their full electronic health records. It argues that patients are in the best position to coordinate their care across different specialists and institutions, as they are the only common party that interacts with all caregivers. The document also presents some case studies of organizations that have successfully implemented more patient-controlled personal health records, including Great Ormond Street Hospital, UCL Hospital, and Novartis. It envisions a future where patients can take a more active role in managing their health data and sharing information with clinicians.
Data Analytics Project proposal: Smart home based ambient assisted living - D...Tarun Swarup
In Ambient Assisted Living environments, monitoring the elderly population can detect a wide range of environmental and user-specific parameters such as daily activities, a regular period of inactivity, usual behavioural patterns and other basic routines. The prime goal of this proposal is to experiment the anomaly detection methods and clustering techniques such as K-means, local outlier factor, K-nearest, DBSCAN and CURE on data and determine the most efficient and accurate method among all.
Mike Jackson, Chairman of Shaping Tomorrow, presented on the future of healthcare. Key points include:
1) Healthcare systems have lagged 10 years in translating clinical research into practice, neglecting major health issues. Continuous scanning is needed to enable preventative and predictive care.
2) Future healthcare will be predictive, preventative, precise, participatory and personalized through technologies like genomics, digital implants, and mobile health monitoring.
3) By 2025, patients will be at the center of their own care, aided by new technologies, while universal genetics and regenerative medicine become standard. Healthcare will increasingly shift to the home instead of institutions.
mHealth Israel_Dr. Marvin Slepian_ Innovation: A Vital Ingredient for the Ad...Levi Shapiro
To remain as an effective leading force in the US, world-wide and society in general, Medicine has to actively adopt Innovation in its teaching and culture, rather than letting it occur passively. Dr. Slepian discusses Innovation Thinking and Science for addressing the enormous healthcare challenges facing the US.
Innovation is needed to overcome the many stresses that exist
on Medicine today - increased prevention, better Dxics and Txics
cost-effectiveness, increased access to care
1. Multiple sclerosis (MS) is a chronic disease of the central nervous system affecting young adults that causes progressive motor and cognitive deterioration.
2. The pathogenesis of MS is not fully understood but is thought to involve an interaction of environmental, epigenetic, and genetic factors triggering the disease in susceptible individuals.
3. Efforts are focusing on identifying biomarkers that can optimize disease management and improve prognosis.
Design of a Clinical Decision Support System Framework for the Diagnosis and ...Editor IJCATR
This paper proposes an adaptive framework for a Knowledge Based Intelligent Clinical Decision Support System for the
prediction of hepatitis B which is one of the most deadly viral infections that has a monumental effect on the health of people afflicted
with it and has for long remained a perennial health problem affecting a significant number of people the world over. In the framework
the patient information is fed into the system; the Knowledge base stores all the information to be used by the Clinical Decision
Support System and the classification/prediction algorithm chosen after a thorough evaluation of relevant classification algorithms for
this work is the C4.5 Decision Tree Algorithm with its percentage of correctly classified instances given as 61.0734%; it searches the
Knowledge base recursively and matches the patient information with the pertinent rules that suit each case and thereafter gives the
most precise prediction as to whether the patient is prone to hepatitis B or not. This approach to the prediction of hepatitis B provides a
very potent solution to the problem of determining if a person has the likelihood of developing this dreaded illness or is almost not
susceptible to the ailment.
The Saudi Human Genome Program (SHGP) aims to sequence 100,000 human genomes over five years to study genetic diseases in Saudi Arabia. Genetic diseases have a high burden in Saudi Arabia due to high rates of marriage between relatives. The SHGP was established to identify disease-causing genes and variants specific to the Saudi population using next-generation sequencing across genome centers. It has sequenced over 5,000 samples so far and aims to establish a genomic knowledge database to enable personalized medicine and screening efforts in Saudi Arabia.
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"CTSI at UCSF
Keith R. Yamamoto, PhD — Opening Remarks – Precision Medicine
Vice Chancellor for Research
Executive Vice Dean of the School of Medicine
Professor of Cellular and Molecular Pharmacology
UCSF
1) The document discusses the Future Health department at KU Leuven which conducts research in health decision support for professionals, patients, and policymakers.
2) The department takes an interdisciplinary approach and focuses on using data mining, IT, and software design to extract appropriate information from clinical, biomedical, and other health data sources to provide decision support.
3) The goal is to enable better, more cost effective healthcare by providing personalized decision support that is evidence-based, user-centered, and looks ahead to future needs.
The rise of the 'ePatient': how it is affecting clinical practice and research
The document discusses how engaged patients, or "ePatients", who actively gather their own health data and conduct their own research are affecting clinical practice and research. It describes how ePatients are empowered through personal health records, diagnostic testing, genomic data, and self-monitoring devices. This shift towards participatory health challenges traditional clinician-led models and will require changes in areas like privacy, education, and how data is integrated into care.
Presentation given by Prof Fernando J Martin-Sanchez at the HISA (Health Informatics Society Australia) event "A Leap into E-Health" - see http://www.hisa.org.au/events/event_details.asp?id=211738 for further details - on 29th February 2012.
Talk entitled "from the Virtual Human to a Digital Me" presented at the Virtual Physiological Human 2012 Conference held at IET Savoy, Savoy Place, London, 18-20 September 2012.
Digital technologies like wireless sensors, genomics, EHRs, mobile apps, and big data analytics can significantly help patients but cannot replace human compassion and advocacy. These technologies can improve patient engagement, access to information, and personalized care. However, the most effective patient advocates will still be human beings who can combine technology tools with qualities like empathy, communication skills, and devotion of time to help patients navigate the healthcare system.
The document discusses making the electronic health record (EHR) a "killer app" that accelerates widespread adoption. It argues that a paradigm shift is needed in EHR concepts, stakeholders, integration across domains, and faster adoption of technology. For the EHR to be a killer app, it must provide patient safety, efficient care, data management, knowledge management, and adaptive workflows. Overcoming challenges like standards, data sharing, and usability will help realize the promise of informatics to improve health globally.
Panel: FROM SMALL TO BIG TO RICH DATA: Dealing with new sources of data in Biomedicine Precision and Participatory Medicine
Fernando J. Martin-Sanchez, Professor and Chair of Health Informatics at Melbourne Medical School, discusses new sources of data in biomedicine including small, big, and rich data. He describes how small data connects people with meaningful insights from big data to be understandable for everyday tasks. Martin-Sanchez also discusses precision medicine, participatory health, and how convergence between the two can help integrate multiple data sources including genomics, the exposome, and digital health to improve disease prevention and treatment outcomes.
The document discusses integrating genomics data and evidence-based medicine into electronic health records (EHRs) for precision healthcare. It notes the gap between what is known and what is done in healthcare. Integrating genomics could help do the right thing for each patient through pharmacogenomics. However, challenges include representing huge volumes of molecular data in a usable way in EHRs. A three step approach is proposed: 1) get genomic data into EHRs in a structured format, 2) use that data for clinical decision support, 3) evaluate outcomes and continually improve the system.
Presentation that gives an overview of the impact of IT on radiology, including the growing role of biomarkers and artificial intelligence and deep learning on the (future) radiology profession. The shift to precision medicine and personalized care are explained, the reasons for a re-definition of radiology are addressed.
This document discusses the concept of participatory health and the role of mobile technologies, known as mHealth. It argues that mHealth will transform healthcare by enabling active participation of patients, providers, and other stakeholders through technologies like mobile phones. This will allow things like continuous communication between visits, accessing health information and decision support at the point of care, remote monitoring for disease management, and financial applications like real-time billing. However, challenges like interoperability and standards must be addressed. The document advocates for providers to prepare for this change by developing mHealth strategies and balancing new technologies with workflow impacts. Overall, mHealth is presented as a way to improve outcomes while reducing costs through more participatory and connected care.
e-Health or no-Health will cover e-health ecosystem challenges, case studies and industry gaps, and the importance of low power and reliable sensors for better healthcare.
Quick outlook around E-Health and will cover e-health ecosystem challenges, case studies and industry gaps, and the importance of low power and reliable sensors for better healthcare.
Mie2014 workshop: Gap Analysis of Personalized Health Services through Patien...Pei-Yun Sabrina Hsueh
Gap Analysis of Insight-Driven Personalized Health Services through Patient-Controlled Devices
Pei-Yun Sabrina HSUEH, , Michael MARSCHOLLEK, Yardena PERES, Stefan von CAVALLAR and Fernando J. MARTIN-SANCHEZ
IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
Hannover Medical School, Germany
IBM Research Lab in Haifa, Israel
IBM Research Lab in Melbourne, Australia
Melbourne Medical School, Australia
Mobile computing, wearable and embedded tech entail new and different styles of healthcare data processing, clinical and wellness decision support, and patient engagement schemes. This is especially important to the preventive and disease management scenarios that require better understanding of disease progression previously unable to achieve due to the lack of reliable means to capture granular patient-generated data in non-clinical settings. The new sources of data, when coupled with a framework to integrate analytical insights with feasible service models, enable reliable detection of inflection points, habit formation cycles and assessments of treatment efficacy. Research into data collection, recording, management and analysis of behavioral manisfestations and triggers will help address these challenges in areas spanning from simple fall detection to situations requiring complicated, multi-modal health monitoring such as Alzheimer’s progression and other adherence management cases. Leveraging recent advance in health devices and sensors as well as expertise in healthcare practice and informatics, the proposed workshop will help form a deeper understanding of requirements on patient-controlled devices to address unique healthcare challenges, identify care flow gaps and translate these findings to the design of platforms for patient-controlled devices and a portfolio of potential service models for preventive care and disease management.
This document discusses integrated health monitoring and precision medicine. It defines precision medicine as using big data, clinical, molecular, environmental, and behavioral information to understand disease and improve prevention and treatment outcomes for patients. Integrated health monitoring combines data from various sources like personal health records, sensors, genomics, and environmental exposures to develop a dynamic model of a patient's health over time. Health informatics plays a key role in building systems to integrate these diverse data sources and enable precision medicine approaches.
CORD Rare Drug Conference, June 8 - 9, 2022
Opportunities and Challenges for Data Management Real-World Data and Real-World Evidence
• Patient support programs: Sandra Anderson, Innomar Strategies
• AI for Data Management and Enhancement: Aaron Leibtag, Pentavere
• Patient Support and RWE: Laurie Lambert, CADTH
This document provides an overview of digital health for nursing students. It defines digital health and discusses key areas like big data, genomics, and artificial intelligence. It outlines drivers of digital health in India like lifestyle diseases and an aging population. Key aspects of digital health are discussed, including telemedicine, electronic health records, robot-assisted surgery, self-monitoring devices, the internet of medical things, and mHealth. The future of digital health in India is seen to involve expanded telemedicine, electronic medical records, artificial intelligence, and more. Digital health tools were also discussed in the context of COVID-19, along with advantages and challenges of digital health.
Presentation given at Health Informatics and Knowledge Management conference
(http://publichealth.curtin.edu.au/HIKM/), as part of Australasian Computer Science Week 2012.
http://www.cs.rmit.edu.au/acsw2012/
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This document outlines a presentation on digital medicine and new challenges for health informatics. It discusses how digital technologies are converging with medicine and impacting patients through wearables, apps, direct-to-consumer services, and social networks. Precision medicine and participatory health are highlighted as key research areas. The role of biomedical informatics is examined in relation to social media, self-quantification, and exposome informatics. Research being conducted at HaBIC and potential frameworks for understanding quantified self data and its therapeutic benefits are summarized.
This document summarizes a presentation on new sources of big data for precision medicine. It discusses how new data sources like genomics, the human microbiome, epigenomics, and the exposome are generating large amounts of data. It then covers the evolution of precision medicine from concepts like personalized medicine and how strategic initiatives in the UK and US are supporting precision medicine research through funding programs and projects like the Cancer Genome Atlas, eMERGE, and exposome studies. The presentation raises the question of whether we are ready for precision medicine given these new data sources and research efforts.
The Health and Biomedical Informatics Centre (HaBIC) conducts activities in education, translational research informatics, e-health and participatory health research, informatics for precision medicine research, and engagement. Key activities include developing education strategies in health and biomedical informatics, providing expertise and tools to support health data collection and management for research, conducting e-health and participatory health research on topics like telehealth and self-quantification, facilitating precision medicine through genomic and clinical data integration, and engaging with partners in biomedical research institutes, hospitals, and universities.
1) The document discusses self-quantification systems and big data prospects and challenges from these systems. It describes the quantified self movement and tools people use to self-monitor health metrics and experiences.
2) Various types of self-monitoring devices, sensors, and services are presented. Challenges with self-quantification include privacy, security, education, and ensuring data is used for health improvement rather than risk profiling.
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This document provides an overview of nursing informatics (NI). It defines NI as the science and practice that integrates nursing, information and knowledge, with management of information and communication technologies to promote health. The document discusses the evolution of NI as a clinical specialty since the 1970s. It also outlines some of the core skills and roles in NI, including systems analysis, project management, education, research, and technology development.
This document provides an overview of a new postgraduate elective subject on eHealth and Biomedical Informatics Systems. The subject introduces current approaches and future directions in eHealth and healthcare informatics. Topics covered include electronic health records, health portals, telehealth, and privacy/security standards. The subject aims to help students critically evaluate new health technologies, synthesize technical and social factors in informatics projects, and assess competency needs. Assessment consists of a knowledge test, critical appraisal assignment, and project report with presentation. The subject provides foundational knowledge in biomedicine, computing, and information science relevant to the field of health informatics.
The Master of Information Technology Specialisation in Health is a 1-2 year program that trains students in health IT to address the growing demand and shortage of skilled professionals. The program provides a foundation in core IT subjects as well as specialised subjects in areas like eHealth, biomedical informatics, and health data. Students learn from experts in IT and health and have opportunities for industry projects and placements in the biomedical precinct at the University of Melbourne.
In June this year, Prof Martin-Sanchez traveled to Heidelberg, Germany to represent HBIR and University of Melbourne participating in a three day scientific symposium "Biomedical Informatics: Confluence of Multiple Disciplines”.
These are the slides from the presentation he gave to the symposium.
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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 lead (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
6. Describe the flow of current around the heart during the cardiac cycle
7. Discuss the placement and polarity of the leads of electrocardiograph
8. Describe the normal electrocardiograms recorded from the limb leads and explain the physiological basis of the different records that are obtained
9. Define mean electrical vector (axis) of the heart and give the normal range
10. Define the mean QRS vector
11. Describe the axes of leads (hexagonal reference system)
12. Comprehend the vectorial analysis of the normal ECG
13. Determine the mean electrical axis of the ventricular QRS and appreciate the mean axis deviation
14. Explain the concepts of current of injury, J point, and their significance
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. Chapter 3, Cardiology Explained, https://www.ncbi.nlm.nih.gov/books/NBK2214/
7. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
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Health Informatics and Broadband Presentation
1. Health
informa.cs
Fernando
Mar*n-‐Sanchez
Ins$tute
for
a
Broadband-‐Enabled
Society
&
Melbourne
Medical
School
2. Introduc$on
• Broadband
can
provide
many
opportuni$es
for
the
health
sector:
– Improving
youth
mental
health
and
aged
care
services
– Monitoring
health
condi$ons
– Enabling
shared
electronic
health
records
• Broadband
technologies
are
revolu$onising
the
delivery
of
health
care.
Convergence
with
other
technologies
towards
Digitally
Enabled
Personalized
Medicine
3. Aging
Well
– Mobile
and
broadband
technologies
for
ameliora.ng
social
isola.on
in
older
people
– Smart
Homes
for
the
Elderly
–
recent
developments
in
Korea
Youth
Mental
Health
− HORYZONS:
Online
Recovery
for
Youth
Onset
Psychosis
4. Telehealth
– Individual
Electronic
Health
Records
– The
Telestroke
Study
– Hap*c
Tele-‐Rehabilita/on
– Teleden/stry
– Virtual
visits:
Inves*ga*ng
the
acceptability
of
webcam
consulta*ons
for
young
adults’
sexual
health
– Wireless
broadband
monitoring
of
knee
osteoarthri/s
– Overcoming
geographical
barriers
for
community
health
– Interpreter
mediated
cogni*ve
assessments
using
video
conferencing
soFware
– SeeCare
IPTV:
Personalised
Health
Literacy
Demonstrator
– Mobile
Augmented
Reality
– Interpreter
mediated
cogni/ve
assessments
using
video
conferencing
soFware
– High
resolu*on
monitoring
of
atmospheric
pollutants
to
iden*fy
their
impact
on
popula*on
health
– Overcoming
geographical
barriers
for
community
health
– Using
video-‐conferencing
to
pilot
an
educa*on
and
clinical
support
package
for
rural
GPs
in
Mildura
6. Current challenges in Medicine
• Need
of
earlier
diagnosis
• More
personalized
therapies
• Risk
profiling,
disease
predic$on
and
preven$on
• Improve
disease
classifica$on
systems
• Control
health
system
costs
• Clinical
trials
and
the
development
of
new
drugs
need
to
be
more
agile
and
effec$ve.
• Ci$zens
could
take
more
responsibility
for
the
maintenance
of
their
own
health.
• Shortage
of
health
professionals
7. The Digitalization of Medicine
• Digital
revolu$on
in
other
domains
(banking,
insurance,
leisure,
government,…)
• The
incorpora$on
of
digital
systems
in
healthcare
is
lagging
behind
other
sectors:
– Reasons:
complexity,
privacy,
volume
of
data,
lack
of
demand
– It
has
greatly
affected
healthcare
at
the
hospital
or
research
centre
level.
– The
digital
revolu$on
has
not
yet
reached
medicine,
at
the
pa$ent/ci$zen
level
• BUT
THIS
IS
STARTING
TO
HAPPEN
NOW
!!!
8. Enabling scientific and
technological advancements
• New
converging
areas
make
feasible
for
the
first
$me
the
idea
of
an
integrated
digital
infrastructure
for
medicine,
reaching
the
ci$zen,
that
will
make
feasible
the
concept
of
personalized
medicine
– Nanotechnology
– Biotechnology
– Informa$on
Technologies
– Cogni$ve
science
9. Enabling scientific and
technological advancements
• Broadband
technologies
and
networks
• High
performance
compu$ng
(and
A.I.
systems)
• Ubiquity
of
smartphones,
tablets,
…
• Sensors,
imaging
and
wearables
• Personal
genome
sequencing,
gene$c
tes$ng
and
epigene$cs
• Metagenomics
and
the
Human
Microbiome
Project
• Social
networks
and
the
Quan$fied
Self
• Knowledge
management
on
gene$c
diseases
and
systems
biology
modelling
10. Smartphone apps
• Smartphone
ECG
system
to
provide
physicians
and
pa$ents
with
hospital-‐quality
heart
rhythm
monitoring
outside
of
the
hospital
se`ng
11. Advances in genomic
technology
• Benchtop
Ion
Proton™
Sequencer
–
designed
to
sequence
the
en$re
human
genome
in
a
day
for
$1,000
12. Graphs of my total cholesterol (blue), my “bad” LDL cholesterol (red),
and my “good” cholesterol (green) over a decade.
(Larry Smarr, CalTech)
13. Remote
pa$ent
data
monitoring
and
data
collec$on
Environmental sensors Genomic sensors
Phenomic sensors
Environmental risk factors Biomarkers (DNA sequence,
(pollution, radiation, toxic agents, …) proteins, gene expression, epigenetics
Physiological, biochemical parameters
(cholesterol, temperature, glucose, heart rate…)
Integrated personal health record
14. Digitally
enabled
personalised
medicine
• Personalized
medicine
refers
to
the
tailoring
of
medical
treatment
to
groups
of
pa$ents
with
similar
gene$c
or
molecular
profiles.
• Ultra
high
speed
broadband
networks
will
be
required
to
transmit
enormous
volumes
of
data
from
pa$ents’
homes
to
health
prac$$oners
and
vice
versa
in
a
$mely
manner,
and
to
enable
the
processing
of
this
deluge
of
data.
• Personalised
medicine
offers
enormous
opportuni$es
for
improving
preven$ve,
diagnos$c
and
therapeu$c
solu$ons
à
improving
healthcare
outcomes,
reducing
costs
and
increasing
pa$ent
safety.
16. Patient Data (sensors and imaging)
Sensors
Genomic Phenomic Environmental
Integrated Personal
EHR Health Record
Module 1 Health Profile GWAS
Assessment
Tables (weighted factors)
Modelling Risks
Diagnosis Personal
Health Profile
CDSS
Health Profile
Module 2 Improvement Trialbanks
NBN
Risk reduction Decision matrix, protocols
Follow-up Personalised
Therapy Health Recommendations
17. Social
media
and
biomedical
and
clinical
research
• We
are
witnessing
a
transi$on
from
research
informa$on
systems
centralized
at
hospitals
and
clinical
research
centres
to
distributed
systems
that
reach
out
to
the
residence
of
any
ci$zen
/
pa$ent
who
opts
in.
• Social
media
as
a
research
tool
• Clinical
Research
with
the
pa$ents,
not
on
the
pa$ents
• Examples
– 23andMe
–
Parkinson’s
Disease
–
PLoS
Gene$cs,
2
new
gene$c
associa$ons
– Pa$entsLikeMe
–
Nature
Biotech.
Self-‐reported
data
from
600
pa$ents
on
the
use
of
lithium
for
Amyotrophic
Lateral
Sclerosis
(ALS)
18. Pa$ent
empowerment
Current NBN-enabled Driving forces: patient empowerment,
networks personalized medicine, social networks
EHR – Personally Citizens are able to maintain and control
Electronic Controlled EHR their own health information
Health Record
Gene-disease Personal Citizens ask for genetic analysis of their
association genomics DNA through the Internet and receive
studies reports on various aspects of their health
Clinical trials Crowdsourced The patient voluntarily shares information
clinical trials on treatments and evolution of his/her
illness with other patients
19. Barriers
• New
regulatory
framework
(new
models
of
clinical
trials)
• New
informa$cs
methods
to
compile
and
interpret
all
the
informa$on
• Educa$on
of
pa$ents
and
health
professionals
• Ethics,
data
security
and
confiden$ality
issues
• Wide
availability
of
clinical
decision
support
systems
at
the
point-‐of-‐care
• New
cost-‐effec$veness
assessment
and
financial
models
of
care
• Need
to
prove
clinical
effec$veness
before
DTC
services
are
offered.
20. Conclusions
• The
rou$ne
applica$on
of
personalised
medicine
is
s$ll
a
long
way
ahead,
however
we
have
now
all
the
ingredients
to
make
it
happen.
• The
convergence
of
medicine
and
the
digital
revolu$on
will
produce
an
informa.on
ecosystem
that
will
facilitate
the
advent
of
safer
and
more
efficient
preven$ve,
diagnos$c
and
therapeu$c
solu$ons.
• The
ci$zen
will
have
access
to
her
gene.c
profile
and
clinical
record,
and
will
monitor
and
adjust
her
health
using
next
genera$on
sensors
and
social
networks
to
share
this
informa$on
with
peers,
clinicians
and
researchers.
Virtual
pa$ent
–
Pa$ent
avatar
21. Conclusions
• But
all
of
this
will
only
be
possible
if
we
realise
that
it
is
.me
for
us
to
take
responsibility
for
our
own
health.
– “The
Crea$ve
Destruc$on
of
Medicine”
(Topol),
–
“Networked
individualism”
(Rainie),
or
–
“P4
Medicine”
(Hood).
• We
prefer
the
term
“Digitally
enabled
personalized
medicine”
and
have
already
started
research
work
in
several
areas:
clinical
genomics,
modelling
and
the
use
of
social
media
for
biomedical
research.
• We
believe
that
the
synergy
between
Health
Informa$cs
and
the
broadband
network
in
the
context
of
mul$disciplinary
collabora$on
and
innova$on
offered
by
Carlton
Connect
will
contribute
to
accelerate
the
advent
of
personalised
medicine.
22. Thank
you
oms@unimelb.edu.au
www.healthinforma$cs.unimelb.edu.au
Twiqer:
@ibeshbir