An overview of the role of information and communication technologies in health and development with implications for global violence prevention efforts for an Institute of Medicine workshop, December 2011.
mHealth, social media, and non-communicable diseases (NCDs)
The document discusses how mHealth applications and social media can help address NCDs. Several specific applications are highlighted that use social media, games, or sensors to help with conditions like diabetes, cardiovascular disease, asthma, and dengue. Opportunities for leveraging existing platforms, integrating with other health interventions, and learning from social networks are discussed. The future of mHealth may involve more peer-to-peer interventions as smartphone use increases in developing areas.
Kno.e.sis Approach to Impactful Research & Training for Exceptional CareersAmit Sheth
Abstract
Kno.e.sis (http://knoesis.org) is a world-class research center that uses semantic, cognitive, and perceptual computing for gathering insights from physical/IoT, cyber/Web, and social and enterprise (e.g., clinical) big data. We innovate and employ semantic web, machine learning, NLP/IR, data mining, network science and highly scalable computing techniques. Our highly interdisciplinary research impacts health and clinical applications, biomedical and translational research, epidemiology, cognitive science, social good, policy, development, etc. A majority of our $12+ million in active funds come from the NSF and NIH. In this talk, I will provide an overview of some of our major research projects.
Kno.e.sis is highly successful in its primary mission of exceptional student outcomes: our students have exceptional publication and real-world impact and our PhDs compete with their counterparts from top 10 schools for initial jobs in research universities, top industry research labs, and highly competitive companies. A key reason for Kno.e.sis' success is its unique work culture involving teamwork to solve complex problems. Practically all our work involves real-world challenges, real-world data, interdisciplinary collaborators, path-breaking research to solve challenges, real-world deployments, real-world use, and measurable real-world impact.
In this talk, I will also seek to discuss our choice of research topics and our unique ecosystem that prepares our students for exceptional careers.
MHealth Mobile Mondays Panel Discussion - Sept 2013 Glenn Roland
This document summarizes opportunities and challenges in the field of mHealth. It discusses how mHealth is defined as using mobile devices like phones and tablets for healthcare services. The opportunities in mHealth include advances in networks and devices, healthcare reform goals to lower costs, and growing digital health investment and apps. However, challenges exist around FDA oversight of medical apps and risks from patent assertion entities pursuing litigation. Overall venture funding for digital health remains strong with the market for mHealth apps expected to reach $26 billion by 2017.
Augmented Personalized Health: using AI techniques on semantically integrated...Amit Sheth
Keynote @ 2018 AAAI Joint Workshop on Health Intelligence (W3PHIAI 2018), 2 February 2018, New Orleans, LA [Video: https://youtu.be/GujvoWRa0O8]
Related article: https://ieeexplore.ieee.org/document/8355891/
Abstract
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease-focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven. While the ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. In this talk, we will discuss how use of AI techniques on semantically integrated patient-generated health data (PGHD), environmental data, clinical data, and public social data is exploited to achieve a range of augmented health management strategies that include self-monitoring, self-appraisal, self-management, intervention, and Disease Progression Tracking and Prediction. We will review examples and outcomes from a number of applications, some involving patient evaluations, including asthma in children, bariatric surgery/obesity, mental health/depression, that are part of the Kno.e.sis kHealth personalized digital health initiative.
Background: Background: http://bit.ly/k-APH, http://bit.ly/kAsthma, http://j.mp/PARCtalk
Wide adoption of smartphones and availability of low-cost sensors has resulted in seamless and continuous monitoring of physiology, environment, and public health notifications. However, personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context. Contextual processing of patient data along with personalized medical knowledge can lead to actionable information for better and timely decisions. We present a system called kHealth capable of aggregating multisensory and multimodal data from sensors (passive sensing) and answers to questionnaire (active sensing) from patients with asthma. We present our preliminary data analysis comprising data collected from real patients highlighting the challenges in deploying such an application. The results show strong promise to derive actionable information using a combination of physiological indicators from active and passive sensors that can help doctors determine more precisely the cause, severity, and control level of asthma. Information synthesized from kHealth can be used to alert patients and caregivers for seeking timely clinical assistance to better manage asthma and improve their quality of life.
Paper: http://www.knoesis.org/library/resource.php?id=2153
Citation:
Pramod Anantharam, Tanvi Banerjee, Amit Sheth, Krishnaprasad Thirunarayan, Surendra Marupudi, Vaikunth Sridharan, Shalini G. Forbis, Knowledge-driven Personalized Contextual mHealth Service for Asthma Management in Children , IEEE 4th International Conference on Mobile Services, June 27 - July 2, 2015, New York, USA.
Silicon valley and the search for immortality — the future of healthcareYogesh Malik
Digital pills, sensors, and big data will allow doctors, hospitals, and machines to be on the same page and access the right health information to save lives and help people live longer. 3D printing is transforming medicine by printing pills, tissues, and organs tailored to individual needs. Technology is also powering lab-on-a-chip devices, personalized health monitoring tools, and advances in detecting and treating diseases through machine learning and artificial intelligence. The future of healthcare is focused on using these technologies to augment human capabilities and potentially achieve immortality by 2030.
mHealth, social media, and non-communicable diseases (NCDs)
The document discusses how mHealth applications and social media can help address NCDs. Several specific applications are highlighted that use social media, games, or sensors to help with conditions like diabetes, cardiovascular disease, asthma, and dengue. Opportunities for leveraging existing platforms, integrating with other health interventions, and learning from social networks are discussed. The future of mHealth may involve more peer-to-peer interventions as smartphone use increases in developing areas.
Kno.e.sis Approach to Impactful Research & Training for Exceptional CareersAmit Sheth
Abstract
Kno.e.sis (http://knoesis.org) is a world-class research center that uses semantic, cognitive, and perceptual computing for gathering insights from physical/IoT, cyber/Web, and social and enterprise (e.g., clinical) big data. We innovate and employ semantic web, machine learning, NLP/IR, data mining, network science and highly scalable computing techniques. Our highly interdisciplinary research impacts health and clinical applications, biomedical and translational research, epidemiology, cognitive science, social good, policy, development, etc. A majority of our $12+ million in active funds come from the NSF and NIH. In this talk, I will provide an overview of some of our major research projects.
Kno.e.sis is highly successful in its primary mission of exceptional student outcomes: our students have exceptional publication and real-world impact and our PhDs compete with their counterparts from top 10 schools for initial jobs in research universities, top industry research labs, and highly competitive companies. A key reason for Kno.e.sis' success is its unique work culture involving teamwork to solve complex problems. Practically all our work involves real-world challenges, real-world data, interdisciplinary collaborators, path-breaking research to solve challenges, real-world deployments, real-world use, and measurable real-world impact.
In this talk, I will also seek to discuss our choice of research topics and our unique ecosystem that prepares our students for exceptional careers.
MHealth Mobile Mondays Panel Discussion - Sept 2013 Glenn Roland
This document summarizes opportunities and challenges in the field of mHealth. It discusses how mHealth is defined as using mobile devices like phones and tablets for healthcare services. The opportunities in mHealth include advances in networks and devices, healthcare reform goals to lower costs, and growing digital health investment and apps. However, challenges exist around FDA oversight of medical apps and risks from patent assertion entities pursuing litigation. Overall venture funding for digital health remains strong with the market for mHealth apps expected to reach $26 billion by 2017.
Augmented Personalized Health: using AI techniques on semantically integrated...Amit Sheth
Keynote @ 2018 AAAI Joint Workshop on Health Intelligence (W3PHIAI 2018), 2 February 2018, New Orleans, LA [Video: https://youtu.be/GujvoWRa0O8]
Related article: https://ieeexplore.ieee.org/document/8355891/
Abstract
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease-focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven. While the ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. In this talk, we will discuss how use of AI techniques on semantically integrated patient-generated health data (PGHD), environmental data, clinical data, and public social data is exploited to achieve a range of augmented health management strategies that include self-monitoring, self-appraisal, self-management, intervention, and Disease Progression Tracking and Prediction. We will review examples and outcomes from a number of applications, some involving patient evaluations, including asthma in children, bariatric surgery/obesity, mental health/depression, that are part of the Kno.e.sis kHealth personalized digital health initiative.
Background: Background: http://bit.ly/k-APH, http://bit.ly/kAsthma, http://j.mp/PARCtalk
Wide adoption of smartphones and availability of low-cost sensors has resulted in seamless and continuous monitoring of physiology, environment, and public health notifications. However, personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context. Contextual processing of patient data along with personalized medical knowledge can lead to actionable information for better and timely decisions. We present a system called kHealth capable of aggregating multisensory and multimodal data from sensors (passive sensing) and answers to questionnaire (active sensing) from patients with asthma. We present our preliminary data analysis comprising data collected from real patients highlighting the challenges in deploying such an application. The results show strong promise to derive actionable information using a combination of physiological indicators from active and passive sensors that can help doctors determine more precisely the cause, severity, and control level of asthma. Information synthesized from kHealth can be used to alert patients and caregivers for seeking timely clinical assistance to better manage asthma and improve their quality of life.
Paper: http://www.knoesis.org/library/resource.php?id=2153
Citation:
Pramod Anantharam, Tanvi Banerjee, Amit Sheth, Krishnaprasad Thirunarayan, Surendra Marupudi, Vaikunth Sridharan, Shalini G. Forbis, Knowledge-driven Personalized Contextual mHealth Service for Asthma Management in Children , IEEE 4th International Conference on Mobile Services, June 27 - July 2, 2015, New York, USA.
Silicon valley and the search for immortality — the future of healthcareYogesh Malik
Digital pills, sensors, and big data will allow doctors, hospitals, and machines to be on the same page and access the right health information to save lives and help people live longer. 3D printing is transforming medicine by printing pills, tissues, and organs tailored to individual needs. Technology is also powering lab-on-a-chip devices, personalized health monitoring tools, and advances in detecting and treating diseases through machine learning and artificial intelligence. The future of healthcare is focused on using these technologies to augment human capabilities and potentially achieve immortality by 2030.
Ehealth: enabling self-management, public health 2.0 and citizen scienceKathleen Gray
Invited presentation, Technology in Diabetes Joint Symposium, Australian Diabetes Society & Australian Diabetes Educators Association Annual Scientific Meeting, August 2014.
This document discusses the future of connected health and how technology can help solve problems in healthcare. It describes how connected devices, sharing health data, and social networks can help create an ecosystem that democratizes health knowledge. This ecosystem will treat health as an information science and see people as "biocitizens" sharing their data. It will lead to an algorithmic revolution that manages knowledge and exploits social networks to reconceptualize the healthcare enterprise.
kHealth Bariatrics is an effort to bout against weight recidivism post bariatric surgery. The computer scientists working at Kno.e.sis, an Ohio Center of Excellence in BioHealth Innovation, are collaborating with a bariatric surgeon and a behavioural specialist to bolster weight loss surgery patients for appropriate postsurgical progress.
The document discusses researching large-scale IT programs in healthcare and proposes a new theoretical approach. It introduces structuration theory and actor-network theory to help conceptualize what happens at both the macro and micro levels when networked health record systems are introduced. While such systems aim to modernize and improve care, the outcomes are complex and unpredictable. New theories are needed to illuminate how social structures, individual actions, and technologies interact and evolve in nonlinear ways.
The document discusses whether the emergence of mHealth (mobile health applications and technologies) can help drive healthcare delivery towards more consumer-centered models. It notes the large number of mobile subscriptions worldwide and increasing number of health-related apps, but also highlights challenges like privacy, security, interoperability, and ensuring access for elderly populations not comfortable with technology. While mHealth shows potential, more evidence is still needed on its impact and how well it can improve healthcare delivery under different circumstances. Stakeholder collaboration will also be important to increase adoption of mHealth. Overall, it remains unclear whether mHealth will revolutionize healthcare or be a passing trend.
Social media and computing technologies are becoming increasingly important tools for healthcare organizations and consumers. They allow for information sharing, online support groups, and new ways of engaging patients. As patients become more active researchers, the relationship with providers will shift from authoritative to a partnership model. New sites also use crowdsourcing techniques to diagnose patients by collecting opinions from medical experts and laypeople. While not a replacement for doctors, these methods could potentially identify new diagnosis options more cheaply than specialist visits alone.
Presentation of Hexoskin Validation for KHealth's Dementia Project
The paper is available at: http://www.knoesis.org/library/resource.php?id=2155
Citation for the paper: T. Banerjee, P. Anantharam, W. L. Romine, L. Lawhorne, A. Sheth, 'Evaluating a Potential Commercial Tool for Healthcare Application for People with Dementia' in Proc. of the Intl Conf on Health Informatics and Medical Systems (HIMS), Las Vegas, July 27-30, 2015.
A presentation at Data Driven Connecticut 2014: Progress and Possibilities. Moving from Data to Action: A Connecticut Data Collaborative Conference on Friday, November 24, 2014 at Yale School of Management, Evans Hall, New Haven, Connecticut. See Notes for presentation script.
The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine's Compueter Age3GDR
This document summarizes a presentation by Robert Wachter on the challenges and opportunities of health information technology. It discusses how digitizing medical records and connecting different clinical systems has been difficult and disrupted existing workflows. While technology holds promise, unlocking its full benefits will require reimagining clinical work and addressing "adaptive challenges" like changing culture and skills. Realizing gains will take overcoming resistance to change, integrating different technologies, and focusing on decision support over mere digitization.
Meeting healthcare challenges: what are the challenges and what is the role o...Mohammad Al-Ubaydli
The document discusses the challenges facing healthcare systems and the role that e-health can play in addressing these challenges. The major challenges are quality and safety, access, responsiveness, and affordability. E-health can help by providing access to electronic patient records, reducing complexity, optimizing information processing, and increasing efficiency. It can also help with navigation through the healthcare system and engaging patients in their own health. The document advocates for free access to research information and using data to identify at-risk patients in need of care.
The document discusses the future of participatory and patient-driven health initiatives. It outlines several emerging models including social media for health, smartphone health apps, personal health records, personalized genomics, crowdsourced health studies, and next-generation participatory approaches. The increasing role of patients and citizens in their own health research and care is driven by new technologies that lower costs and facilitate sharing of data.
TRILcon'17 confernece workshop presentation on UnBias stakeholder engagementAnsgar Koene
Presentation outlining the stakeholder engagement activities of the UnBias project, including case study driven debate with participants at the Winchester TRILcon conference on May 3rd 2017
Understanding users’ latent intents behind search queries is essential for satisfying a user’s search needs. Search intent mining can help search engines to enhance its ranking of search results, enabling new search features like instant answers, personalization, search result diversification, and the recommendation of more relevant ads. Consequently, there has been increasing attention on studying how to effectively mine search intents by analyzing search engine query logs. While state-of-the-art techniques can identify the domain of the queries (e.g. sports, movies, health), identifying domain-specific intent is still an open problem. Among all the topics available on the Internet, health is one of the most important in terms of impact on the user and it is one of the most frequently searched areas. This dissertation presents a knowledge-driven approach for domain-specific search intent mining with a focus on health-related search queries.
First, we identified 14 consumer-oriented health search intent classes based on inputs from focus group studies and based on analyses of popular health websites, literature surveys, and an empirical study of search queries. We defined the problem of classifying millions of health search queries into zero or more intent classes as a multi-label classification problem. Popular machine learning approaches for multi-label classification tasks (namely, problem transformation and algorithm adaptation methods) were not feasible due to the limitation of label data creations and health domain constraints. Another challenge in solving the search intent identification problem was mapping terms used by laymen to medical terms. To address these challenges, we developed a semantics-driven, rule-based search intent mining approach leveraging rich background knowledge encoded in Unified Medical Language System (UMLS) and a crowd sourced encyclopedia (Wikipedia). The approach can identify search intent in a disease-agnostic manner and has been evaluated on three major diseases.
While users often turn to search engines to learn about health conditions, a surprising amount of health information is also shared and consumed via social media, such as public social platforms like Twitter. Although Twitter is an excellent information source, the identification of informative tweets from the deluge of tweets is the major challenge. We used a hybrid approach consisting of supervised machine learning, rule-based classifiers, and biomedical domain knowledge to facilitate the retrieval of relevant and reliable health information shared on Twitter in real time. Furthermore, we extended our search intent mining algorithm to classify health-related tweets into health categories. Finally, we performed a large-scale study to compare health search intents and features that contribute in the expression of search intent from 100+ million search queries from smarts devices (smartphones/tablets) and personal computers (desktops/laptops)
This document discusses the concept of eHealth (internet and health) from several perspectives. It defines eHealth and explores its potential benefits, including increased efficiency, quality of care, evidence-based practices, and patient empowerment. Challenges like equity and ethics are also addressed. Real-world data on internet usage for health purposes is presented. Overall the document provides an overview of the emerging field of eHealth.
Promise and peril: How artificial intelligence is transforming health careΔρ. Γιώργος K. Κασάπης
AI has enormous potential to improve the quality of health care, enable early diagnosis of diseases, and reduce costs. But if implemented incautiously, AI can exacerbate health disparities, endanger patient privacy, and perpetuate bias. STAT, with support from the Commonwealth Fund, explored these possibilities and pitfalls during the past year and a half, illuminating best practices while identifying concerns and regulatory gaps. This report includes many of the articles we published and summarizes our findings, as well as recommendations we heard from caregivers, health care executives, academic experts, patient advocates, and others.
Infrastructure of an informatics department4tanyasbrown
This document discusses the infrastructure of an informatics department. It defines informatics as a bridge between technology and a specific domain like health. It explains that health informatics is the study of designing, developing, adopting, and applying IT innovations in healthcare services, delivery, management and planning. The document also discusses the Patient Protection and Affordable Care Act and how it has led to changes like the increased use of electronic medical records at both the local and national levels in healthcare.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document discusses social innovation and changing models of scientific innovation. It notes that in African sign language, the sign for the future points backward, indicating the future is understood through the past. It also discusses tensions between democratization and privatization and mentions citizen scientists, knowledge systems in Africa, and representations of innovation and knowledge. Key themes are social innovation, viewing the future as combining old and new, harnessing people as infrastructure, constraints spurring innovation, and changing practices and models in science through open science and networks.
Ehealth: enabling self-management, public health 2.0 and citizen scienceKathleen Gray
Invited presentation, Technology in Diabetes Joint Symposium, Australian Diabetes Society & Australian Diabetes Educators Association Annual Scientific Meeting, August 2014.
This document discusses the future of connected health and how technology can help solve problems in healthcare. It describes how connected devices, sharing health data, and social networks can help create an ecosystem that democratizes health knowledge. This ecosystem will treat health as an information science and see people as "biocitizens" sharing their data. It will lead to an algorithmic revolution that manages knowledge and exploits social networks to reconceptualize the healthcare enterprise.
kHealth Bariatrics is an effort to bout against weight recidivism post bariatric surgery. The computer scientists working at Kno.e.sis, an Ohio Center of Excellence in BioHealth Innovation, are collaborating with a bariatric surgeon and a behavioural specialist to bolster weight loss surgery patients for appropriate postsurgical progress.
The document discusses researching large-scale IT programs in healthcare and proposes a new theoretical approach. It introduces structuration theory and actor-network theory to help conceptualize what happens at both the macro and micro levels when networked health record systems are introduced. While such systems aim to modernize and improve care, the outcomes are complex and unpredictable. New theories are needed to illuminate how social structures, individual actions, and technologies interact and evolve in nonlinear ways.
The document discusses whether the emergence of mHealth (mobile health applications and technologies) can help drive healthcare delivery towards more consumer-centered models. It notes the large number of mobile subscriptions worldwide and increasing number of health-related apps, but also highlights challenges like privacy, security, interoperability, and ensuring access for elderly populations not comfortable with technology. While mHealth shows potential, more evidence is still needed on its impact and how well it can improve healthcare delivery under different circumstances. Stakeholder collaboration will also be important to increase adoption of mHealth. Overall, it remains unclear whether mHealth will revolutionize healthcare or be a passing trend.
Social media and computing technologies are becoming increasingly important tools for healthcare organizations and consumers. They allow for information sharing, online support groups, and new ways of engaging patients. As patients become more active researchers, the relationship with providers will shift from authoritative to a partnership model. New sites also use crowdsourcing techniques to diagnose patients by collecting opinions from medical experts and laypeople. While not a replacement for doctors, these methods could potentially identify new diagnosis options more cheaply than specialist visits alone.
Presentation of Hexoskin Validation for KHealth's Dementia Project
The paper is available at: http://www.knoesis.org/library/resource.php?id=2155
Citation for the paper: T. Banerjee, P. Anantharam, W. L. Romine, L. Lawhorne, A. Sheth, 'Evaluating a Potential Commercial Tool for Healthcare Application for People with Dementia' in Proc. of the Intl Conf on Health Informatics and Medical Systems (HIMS), Las Vegas, July 27-30, 2015.
A presentation at Data Driven Connecticut 2014: Progress and Possibilities. Moving from Data to Action: A Connecticut Data Collaborative Conference on Friday, November 24, 2014 at Yale School of Management, Evans Hall, New Haven, Connecticut. See Notes for presentation script.
The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine's Compueter Age3GDR
This document summarizes a presentation by Robert Wachter on the challenges and opportunities of health information technology. It discusses how digitizing medical records and connecting different clinical systems has been difficult and disrupted existing workflows. While technology holds promise, unlocking its full benefits will require reimagining clinical work and addressing "adaptive challenges" like changing culture and skills. Realizing gains will take overcoming resistance to change, integrating different technologies, and focusing on decision support over mere digitization.
Meeting healthcare challenges: what are the challenges and what is the role o...Mohammad Al-Ubaydli
The document discusses the challenges facing healthcare systems and the role that e-health can play in addressing these challenges. The major challenges are quality and safety, access, responsiveness, and affordability. E-health can help by providing access to electronic patient records, reducing complexity, optimizing information processing, and increasing efficiency. It can also help with navigation through the healthcare system and engaging patients in their own health. The document advocates for free access to research information and using data to identify at-risk patients in need of care.
The document discusses the future of participatory and patient-driven health initiatives. It outlines several emerging models including social media for health, smartphone health apps, personal health records, personalized genomics, crowdsourced health studies, and next-generation participatory approaches. The increasing role of patients and citizens in their own health research and care is driven by new technologies that lower costs and facilitate sharing of data.
TRILcon'17 confernece workshop presentation on UnBias stakeholder engagementAnsgar Koene
Presentation outlining the stakeholder engagement activities of the UnBias project, including case study driven debate with participants at the Winchester TRILcon conference on May 3rd 2017
Understanding users’ latent intents behind search queries is essential for satisfying a user’s search needs. Search intent mining can help search engines to enhance its ranking of search results, enabling new search features like instant answers, personalization, search result diversification, and the recommendation of more relevant ads. Consequently, there has been increasing attention on studying how to effectively mine search intents by analyzing search engine query logs. While state-of-the-art techniques can identify the domain of the queries (e.g. sports, movies, health), identifying domain-specific intent is still an open problem. Among all the topics available on the Internet, health is one of the most important in terms of impact on the user and it is one of the most frequently searched areas. This dissertation presents a knowledge-driven approach for domain-specific search intent mining with a focus on health-related search queries.
First, we identified 14 consumer-oriented health search intent classes based on inputs from focus group studies and based on analyses of popular health websites, literature surveys, and an empirical study of search queries. We defined the problem of classifying millions of health search queries into zero or more intent classes as a multi-label classification problem. Popular machine learning approaches for multi-label classification tasks (namely, problem transformation and algorithm adaptation methods) were not feasible due to the limitation of label data creations and health domain constraints. Another challenge in solving the search intent identification problem was mapping terms used by laymen to medical terms. To address these challenges, we developed a semantics-driven, rule-based search intent mining approach leveraging rich background knowledge encoded in Unified Medical Language System (UMLS) and a crowd sourced encyclopedia (Wikipedia). The approach can identify search intent in a disease-agnostic manner and has been evaluated on three major diseases.
While users often turn to search engines to learn about health conditions, a surprising amount of health information is also shared and consumed via social media, such as public social platforms like Twitter. Although Twitter is an excellent information source, the identification of informative tweets from the deluge of tweets is the major challenge. We used a hybrid approach consisting of supervised machine learning, rule-based classifiers, and biomedical domain knowledge to facilitate the retrieval of relevant and reliable health information shared on Twitter in real time. Furthermore, we extended our search intent mining algorithm to classify health-related tweets into health categories. Finally, we performed a large-scale study to compare health search intents and features that contribute in the expression of search intent from 100+ million search queries from smarts devices (smartphones/tablets) and personal computers (desktops/laptops)
This document discusses the concept of eHealth (internet and health) from several perspectives. It defines eHealth and explores its potential benefits, including increased efficiency, quality of care, evidence-based practices, and patient empowerment. Challenges like equity and ethics are also addressed. Real-world data on internet usage for health purposes is presented. Overall the document provides an overview of the emerging field of eHealth.
Promise and peril: How artificial intelligence is transforming health careΔρ. Γιώργος K. Κασάπης
AI has enormous potential to improve the quality of health care, enable early diagnosis of diseases, and reduce costs. But if implemented incautiously, AI can exacerbate health disparities, endanger patient privacy, and perpetuate bias. STAT, with support from the Commonwealth Fund, explored these possibilities and pitfalls during the past year and a half, illuminating best practices while identifying concerns and regulatory gaps. This report includes many of the articles we published and summarizes our findings, as well as recommendations we heard from caregivers, health care executives, academic experts, patient advocates, and others.
Infrastructure of an informatics department4tanyasbrown
This document discusses the infrastructure of an informatics department. It defines informatics as a bridge between technology and a specific domain like health. It explains that health informatics is the study of designing, developing, adopting, and applying IT innovations in healthcare services, delivery, management and planning. The document also discusses the Patient Protection and Affordable Care Act and how it has led to changes like the increased use of electronic medical records at both the local and national levels in healthcare.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document discusses social innovation and changing models of scientific innovation. It notes that in African sign language, the sign for the future points backward, indicating the future is understood through the past. It also discusses tensions between democratization and privatization and mentions citizen scientists, knowledge systems in Africa, and representations of innovation and knowledge. Key themes are social innovation, viewing the future as combining old and new, harnessing people as infrastructure, constraints spurring innovation, and changing practices and models in science through open science and networks.
The document discusses innovation in science and technology in Africa. It argues that the future of innovation is unpredictable and will differ from current expectations. New models of innovation are emerging that emphasize open collaboration, embracing risk and failure, and harnessing both traditional and modern knowledge systems. The document advocates for creating open science networks and commons in Africa to facilitate collaboration, knowledge sharing, and recombinant innovation across multiple stakeholders.
A talk I gave at a Salzburg Global Seminar in 2007 on One World One Health that bridged animal health and public health. Some tech trends and cooperation.
The document discusses the evolution of the web from Web 1.0 to Web 2.0 and open science. Key aspects of Web 2.0 include user-generated content, peer-to-peer interactions, and finding like-minded people. Web 2.0 enables cooperation and problem solving. The document also discusses how science can become more open through tools of Web 2.0 like social media, open access, and crowdsourcing solutions. It raises challenges to enabling more open science in Africa, such as policies prohibiting social tools and lack of bandwidth.
Biosurveillance2.0 ranck digihealth feb 25Jody Ranck
This document discusses how new technologies like crowdsourcing, social networks, and citizen science can enhance biosurveillance and public health through big data. It provides examples like Ushahidi and Google Flu Trends that track diseases. Mobile games and heat maps using machine learning can gather health data. Platforms like InSTEDD and data journalism sites are proliferating. Future challenges include scaling coordinated data sharing for public good while ensuring accuracy, privacy, and governance over this new "data commons". Organizing dynamic health surveillance will require more flexible collaboration beyond traditional control models.
Remixing Public Health: Tools for Public Health InnovationJody Ranck
This document discusses how social media and new technologies can be leveraged for public health goals. It argues that public health approaches need to shift from top-down models to more collaborative models that engage citizens and different sectors. The document outlines various social media tools and platforms that can be used for content creation, collaboration, community-building, and collective action. It provides examples of how these tools have been used for issues like citizen journalism, crisis response, and open data initiatives.
Is there a Blockchain Future for Healthcare?Jody Ranck
Blockchain is a distributed ledger technology that enables decentralized approaches without intermediaries. It has several potential healthcare applications including medical banking to disintermediate counterparties, distributed electronic health records, inventory management, and new models for collaborative data sharing and crowdsourcing. However, challenges remain around transaction throughput, security, regulatory uncertainty, and developing business models to implement blockchain in healthcare.
Big Data, CEP and IoT : Redefining Holistic Healthcare Information Systems an...Tauseef Naquishbandi
Healthcare industry has been a significant area for innovative application of various technologies over decades. Being an area of social relevance governmental spending on healthcare have always been on the rise over the years. Event Processing (CEP) has been in use for many years for situational awareness and response generation. Computing technologies have played an important role in improvising several aspects of healthcare. Recently emergent technology paradigms of Big Data, Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with pain areas of healthcare domain but also to redefine healthcare offerings. This paper aims to lay the groundwork for a healthcare system which builds upon integration of Big Data, CEP and IoT.
The document discusses the potential for citizens to play an increased role in public health through new technologies. It envisions citizens serving as "sentinels" by opting to share personal health data to help public health surveillance. Citizens could also use health data from social networks and devices to connect with others and access health services and programs. New tools are needed to engage citizens as "scientists" by giving them access to and abilities to analyze public health data.
Risk & Opportunities: Healthcare InformationHal Amens
This document outlines risks and opportunities associated with the increasing complexity of health-related information sharing as records move to electronic formats. It notes that while electronic records provide opportunities to capture, store, share and use data in new ways, this also creates new risks from issues like data breaches and defining standards of care. However, the larger databases and connected networks also enable opportunities to more easily find needed information, conduct research across larger populations, and better inform patients and providers. The document acknowledges that while many have discussed these topics, taking a broader view of the many interconnected elements is novel and where risks and opportunities arise.
Overview of Health Informatics: survey of fundamentals of health information technology, Identify the forces behind health informatics, educational and career opportunities in health informatics.
The future interface of mental health with information technology: high touch...HealthXn
The document discusses the future of mental health and technology, including:
- Technology may help address challenges in healthcare systems but also presents pitfalls if not implemented carefully.
- The roles of health professionals and patients may change as technology becomes more integrated in care, requiring new skills.
- Data and information from various sources can provide insights if analyzed properly, but also raise privacy and security concerns.
- Future health systems will rely more on knowledge management and using data/analytics to provide personalized, predictive care while maintaining the human touch.
The document discusses how connected digital tools and data can help augment human capacity in healthcare by providing deep support for patients and populations. It provides examples of how electronic health records, personalized outreach, and remote monitoring have helped improve outcomes for cancer screening, smoking cessation, and symptom management. However, fully realizing the benefits of these technologies will require addressing issues around data integration, communication gaps, and adapting clinical workflows. The goal is to use digital tools to inform and support patients and providers, not replace human relationships and judgment.
Digital Health: Medicine at the CroosroadsSteven Peskin
This document discusses the implications of mobile health and social media in clinical practice. It describes the three components of digital health as applications, devices, and infrastructure. Mobile technologies and social media have tremendous potential to improve care delivery, patient safety, information dissemination, and chronic disease management. The document outlines how physician communities on social media can facilitate knowledge sharing and discusses the growth of medical apps. It predicts that mobile health and social media will become integrated into everyday healthcare through digital tools and communities.
Social Media Datasets for Analysis and Modeling Drug Usageijtsrd
This paper based on the research carried out in the area of data mining depends for managing bulk amount of data with mining in social media on using composite applications for performing more sophisticated analysis. Enhancement of social media may address this need. The objective of this paper is to introduce such type of tool which used in social network to characterised Medicine Usage. This paper outlined a structured approach to analyse social media in order to capture emerging trends in medicine abuse by applying powerful methods like Machine Learning. This paper describes how to fetch important data for analysis from social network. Then big data techniques to extract useful content for analysis are discussed. Sindhu S. B | Dr. B. N Veerappa "Social Media Datasets for Analysis and Modeling Drug Usage" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25246.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/25246/social-media-datasets-for-analysis-and-modeling-drug-usage/sindhu-s-b
Presents a futuristic view based on development in health and medical data processing. the concept of and future of ePatient was discussed. The risks and limitations to digital medicine were presented.
This document discusses the use of deep learning and machine learning techniques in medicine. It begins with an abstract that outlines how advances in computing power and large medical datasets are enabling complex machine learning approaches to be applied to healthcare problems. The document then reviews several examples of early expert systems and machine learning applications in medicine from the 1970s onward. It discusses how machine learning can help with medical tasks like diagnosis, predicting disease risk, and analyzing medical images. However, it also notes that few machine learning systems have meaningfully impacted clinical care. The document explores challenges to adopting these approaches in healthcare and ways to overcome obstacles to changing medical practice through machine learning.
The document discusses 10 megatrends shaping healthcare and healthcare IT over the next 5-10 years based on a meta-analysis of several leading sources. The megatrends are organized into three groups: medicine, politics and society, and technology. Some of the key megatrends discussed include the rise of telemonitoring of patients, personalised medicine enabled by electronic health records, aging populations in western countries, increasing healthcare costs requiring value-based approaches, medical tourism and globalization, the growth of cloud computing and mobile technologies, and emerging fields like robotics and nanotechnology.
Leveraging the Internet of Things to Improve Patient OutcomesAlex Taser
This public thought leader dialogue reinforced that we are in midst of a technology-enabled revolution in healthcare. A world of IoT sensors and the Big Data it enables has the power to personalize and improve care, predict conditions, and enable access and affordable service to previously under-reached communities.
Rather than a sci-fi fantasty, the future of IoT healthcare is already here. While fractured, the technology exists and its capabilities are growing exponentially. The success in ensuring patient health and empowerment hinges on our ability to shift the culture of care, rethink incentives, collaborate across systems, and put the patient voice at the center of it all.
The document discusses how an Internet of Things think tank explored how IoT solutions can improve patient outcomes. Key findings included that connected devices have the potential to benefit patients and providers through predictive analytics, personalized care, improved efficiency and speed of care, and remote patient monitoring. Participants noted big data is important but also raises security and data ownership issues. Ensuring positive outcomes requires collaboration across healthcare stakeholders, putting patients' needs and preferences first, and focusing on ongoing health rather than just care when sick.
Fattori - 50 abstracts of e patient. In collaborazione con Monica DaghioGiuseppe Fattori
This document contains summaries of 50 abstracts related to e-patients and social media. Some key points:
1) Participatory surveillance of hypoglycemia in an online diabetes social network found high rates of hypoglycemic events and related harms like daily worry and withdrawal from activities. Engagement was also high.
2) Analysis of self-reported Parkinson's disease symptom data from an online platform found short-term dynamics like fluctuations exceeding clinically important differences that add to understanding of disease progression.
3) Examination of influential cancer patients on Twitter found most tweets focused on support rather than medical information, indicating its role in online patient community and support.
Swiss Re - Center for Global Dialogue Report: Healthcare revolution: Big dat...Thomas Dijohn
dacadoo is proud to be referenced by Swiss Re - Center of Global Dialogue in report 'Healthcare revolution: Big data and smart analytics'.
dacadoo is referenced in the section "Sensor innovations driving the digital health revolution"
M. Chris Gibbons - Health IT and Healthcare DisparitiesPlain Talk 2015
"Health IT and Healthcare Disparities" was presented at the Center for Health Literacy Conference 2011: Plain Talk in Complex Times by M. Chris Gibbons, MD, MPH, Associate Director, Johns Hopkins Urban Health Institute.
Description: This presenter will discuss the use of technology and consumer health information to improve healthcare disparities.
Artificial intelligence in medicine (projeck)YasserAli152984
The document discusses various uses of artificial intelligence in medicine, including disease detection, diagnostics, scientific experiments, surgery robots, and cancer detection. It notes that AI has made progress in areas like analyzing large datasets, aiding physicians, and automating administrative tasks. However, the integration of human and AI is seen as key to revolutionizing healthcare.
Security of Health Care RecordsWith the increase of health informa.docxkaylee7wsfdubill
Security of Health Care Records
With the increase of health information technology used to store and access patient information, the likelihood of security breaches has also risen. In fact, according to the
Canadian Medical Association Journal
(CMAJ):
In the United States, there was a whopping 97% increase in the number of health records breached from 2010 to 2011… The number of patient records accessed in each breach has also increased substantially, from 26,968 (in 2010) to 49,394 (in 2011). Since August 2009, when the US government regulated that any breach affecting more than 500 patients be publicly disclosed, a total of 385 breaches, involving more than 19 million records, have been reported to the Department of Health and Human Services.
A large portion of those breaches, 39%, occurred because of a lost, stolen, or otherwise compromised portable electronic device—a problem that will likely only get worse as iPads, smartphones, and other gadgets become more common in hospitals. (CMAJ, 2012, p. E215).
Consider your own experiences. Does your organization use portable electronic devices? What safeguards are in place to ensure the security of data and patient information? For this Discussion you consider ethical and security issues surrounding the protection of digital health information.
To prepare:
·
Review the Learning Resources dealing with the security of digital health care information. Reflect on your own organization or one with which you are familiar, and think about how health information stored electronically is protected.
·
Consider the nurse’s responsibility to ensure the protection of patient information. What strategies can you use?
·
Reflect on ethical issues that are likely to arise with the increased access to newer, smaller, and more powerful technology tools.
·
Consider strategies that can be implemented to ensure that the use of HIT contributes to an overall culture of safety.
Post 1 page response APA format ( at least 3 references)
1.
an analysis of the nurse’s responsibility to protect patient information and the extent that HIT has made it easier or more difficult to protect patient privacy.
2.
Comment on any security or ethical issues related to the use of portable devices to store information.
3.
Assess the strategies your organization uses to safeguard patient information and how these promote a culture of safety.
4.
Describe an area where improvement is needed and one strategy that could address the situation.
Course Readings
·
McGonigle, D., & Mastrian, K. G. (2012).
Nursing informatics and the foundation of knowledge
(Laureate Education, Inc., custom ed.). Burlington, MA: Jones and Bartlett Learning.
o
Chapter 5, “Ethical Applications of Informatics”
This chapter examines the ethical dilemmas that arise in nursing informatics. The authors explore the responsibilities for the ethical use of health information technology.
o
Chapter 15, “Information Copyright and Fair Use and Network Securit.
Big data approaches to healthcare systemsShubham Jain
The idea behind this presentation is to explore how big data will revolutionize existing healthcare system effectively by reducing healthcare concerns such as the selection of appropriate treatment paths, quality of healthcare systems and so on. Large amount of unstructured data is available in various organizations (payers, providers, pharmaceuticals). We will discuss all the intricacies involved in massive datasets of healthcare systems and how combination of VPH technologies and big data resulted into some mind-boggling consequences. Major opportunities in healthcare includes the integration of various data pools such as clinical data, pharmaceutical R&D data and patient behaviour and sentiment data. Finding potential insights from big data with the help of medical image processing techniques, predictive modelling etc. will eventually help us to leverage the ever-increasing costs of care, help providers practice more effective medicine, empower patients and caregivers, support fitness and preventive self-care, and to dream about more personalized medicine.
I have framed this talk to encourage Pharmacy students to embrace computing in general, and data science and artificial intelligence techniques in particular. The reason is that data-driven science has overtaken traditional lab science; chemistry and biology that underlie pharmacy have become data-driven sciences, and a significant majority of the new jobs in pharma industries demand data analysis skills. Increasingly, traditional bioinformatics approaches are being complemented or replaced by machine learning or deep learning algorithms, especially for cases that have large data sets. I will provide a few examples (e.g., drug discovery, finding adverse drug reactions and broadly pharmacovigilance, and selecting patients for clinical trials) to demonstrate how big data and/or AI are indispensable to pharma research and industry today.
1. ICTs and the Future of
Public Health
Jody Ranck, DrPH
Institute of Medicine Workshop on ICTs and Global Violence
Prevention
December 8, 2011
2. Key Trends
More pervasive computing power
Cultures of sharing/cooperation
Open Health
Biocitizenship/Technological Citizenship
The rise of the infosphere and the inforg
10. Impact of Social Media
Cultures of sharing
Mashups
Amplification of selves, rapid response
systems/alerts
Connecting to the long tail
Emergence of technological citizenship
11. mHealth
Over 80% of countries have at least one
intervention right now
From Data Collection to Prevention to Acute
Treatment and Transparency
Building the evidence base, many pilots
Next 3 years, more smartphone-based
Ecosystem will change how we think about
health system transformation
12. Continuum of Care
Peer-to-
Diagnostic Acute Long-Term
Prevention Monitoring Peer data
Screening Treatment Treatment
collection
15. Some learnings on
mobiles, gender, violence
The mobile is not a universally appropriate tool
for gender violence---some studies demonstrate
increased risk of violence
Points to the need to look at Gender, Power and
Tech together
Privacy and data, security of SMS
Emerging area of liberation technology may be
useful
23. Open Innovation and
Crowdsourcing
New Skills for Working with Swarms
Interdisciplinarity Transdisciplinarity
Future of work: temporal, modular
New Learning Cultures
32. Rethinking Health
Making the invisible visible
Public engagement with data
From internal medicine to eternal interventions in
the social body
Transdisciplinary: art, design, science,
community participation
Growing Role of Design: Service, Information,
Product
40. A Big Data- Violence Story
In Camden, NJ Dr. Jeffrey Brenner mapped crime
using medical billing data—found care was neither
medically effective nor cost-effective
7 years of data, 600,000 hospital visits
80% of costs associated with 13% of patients
Total cost of $650 million, mostly public funds
Formed Camden Coalition of Healthcare
Providers to address the problem
47. Future of Public Health
New Skills and Literacies for Public Health
Service Design and Change Management
Technological Literacy: shortage of health
informaticians
Business Plans and crossing public-private
divide
Information Architecture and Architecture of
Participation
48. Recap
Participatory Media: democratizing health knowledge and
data
Health is increasingly resembling IT services
New forms of data, uses of data, new data skills
Technology and Culture of Learning
Less hierarchical organizationsNetwork orgs
From command & control to coordinate and cultivate
We are information organismsInforgs
Possibilities for reverse flows in innovation trajectories
Public Health as a Platform—what is the service we can
offer that catalyzes change? And do it, with fewer
resources-disruptive innovation
49.
50. The End
jodyranck@sbcglobal.net
Twitter: jranck
Affiliations: Public Health Institute, GigaOM