National Academies Workshop on Big Data and Analysis for Infectious Disease Research, Operations and Policy.. Pan American Health Organization, Washington, DC (May 11 2016)
Facebook: An Innovative Influenza Pandemic Early Warning SystemChen Luo
Facebook could be used as an innovative system to track influenza pandemics through a social media application. The application would simplify symptom tracking and use Facebook's viral sharing features to rapidly increase participation worldwide. During initial beta testing, over 70% of participants filled out weekly symptom questionnaires. Location data from IP addresses could provide real-time global surveillance of influenza spread. Widespread adoption of the application through media exposure and social sharing is needed for accurate pandemic monitoring on a large scale.
Teamscope presentation - Molecules to Business 2016 Diego Menchaca
The document discusses how mobile health (mHealth) technologies are driving a paradigm shift in clinical research. It describes how electronic data capture (EDC) systems replaced paper-based methods and increased accessibility of data. ResearchKit and the mPower Parkinson's study are highlighted as examples of large mobile clinical studies enabled by accessible app-based data collection. The document argues that mHealth can overcome barriers to clinical research in developing countries by having easy-to-use, offline mobile apps for scalable and low-cost data collection.
A short introduction to raise awareness about the role of NLP in health informatics. The talk aims to briefly describe some of the linguistic and technical challenges in linking texts to knowledge bases/ontologies and present several techniques that we have explored (Limsopatham and Collier, 2016).
An IT Approach to Improve the Compilation of Clinical Access Indicators and D...Editor IJCATR
The proportion of persons visiting a health facility reflects the level of access of that centre to its catchment area in terms of
Out-Patient Department (OPD) per capita. These attendances come with diagnoses which give an indication of the diseases pattern and
prevalence within the catchment area as well as patients who are insured and not insured. Though data of this nature are undisputedly crucial
to public health processes, morbidity returns from most health facilities, particularly public health facilities are generated manually making
it cumbersome and stressful. In addition, this method is error-prone and as such poses a strong threat to disease prevention, control and
information management. This research therefore uses an Information Technology approach to improve the process achieving over 90% time
gain. The Gambaga Health Centre in the East Mamprusi District was selected for the simulation
Significant Role of Statistics in Computational SciencesEditor IJCATR
This paper is focused on the issues related to optimizing statistical approaches in the emerging fields of Computer Science
and Information Technology. More emphasis has been given on the role of statistical techniques in modern data mining. Statistics is
the science of learning from data and of measuring, controlling, and communicating uncertainty. Statistical approaches can play a vital
role for providing significance contribution in the field of software engineering, neural network, data mining, bioinformatics and other
allied fields. Statistical techniques not only helps make scientific models but it quantifies the reliability, reproducibility and general
uncertainty associated with these models. In the current scenario, large amount of data is automatically recorded with computers and
managed with the data base management systems (DBMS) for storage and fast retrieval purpose. The practice of examining large preexisting
databases in order to generate new information is known as data mining. Presently, data mining has attracted substantial
attention in the research and commercial arena which involves applications of a variety of statistical techniques. Twenty years ago
mostly data was collected manually and the data set was in simple form but in present time, there have been considerable changes in
the nature of data. Statistical techniques and computer applications can be utilized to obtain maximum information with the fewest
possible measurements to reduce the cost of data collection.
National Academies Workshop on Big Data and Analysis for Infectious Disease Research, Operations and Policy.. Pan American Health Organization, Washington, DC (May 11 2016)
Facebook: An Innovative Influenza Pandemic Early Warning SystemChen Luo
Facebook could be used as an innovative system to track influenza pandemics through a social media application. The application would simplify symptom tracking and use Facebook's viral sharing features to rapidly increase participation worldwide. During initial beta testing, over 70% of participants filled out weekly symptom questionnaires. Location data from IP addresses could provide real-time global surveillance of influenza spread. Widespread adoption of the application through media exposure and social sharing is needed for accurate pandemic monitoring on a large scale.
Teamscope presentation - Molecules to Business 2016 Diego Menchaca
The document discusses how mobile health (mHealth) technologies are driving a paradigm shift in clinical research. It describes how electronic data capture (EDC) systems replaced paper-based methods and increased accessibility of data. ResearchKit and the mPower Parkinson's study are highlighted as examples of large mobile clinical studies enabled by accessible app-based data collection. The document argues that mHealth can overcome barriers to clinical research in developing countries by having easy-to-use, offline mobile apps for scalable and low-cost data collection.
A short introduction to raise awareness about the role of NLP in health informatics. The talk aims to briefly describe some of the linguistic and technical challenges in linking texts to knowledge bases/ontologies and present several techniques that we have explored (Limsopatham and Collier, 2016).
An IT Approach to Improve the Compilation of Clinical Access Indicators and D...Editor IJCATR
The proportion of persons visiting a health facility reflects the level of access of that centre to its catchment area in terms of
Out-Patient Department (OPD) per capita. These attendances come with diagnoses which give an indication of the diseases pattern and
prevalence within the catchment area as well as patients who are insured and not insured. Though data of this nature are undisputedly crucial
to public health processes, morbidity returns from most health facilities, particularly public health facilities are generated manually making
it cumbersome and stressful. In addition, this method is error-prone and as such poses a strong threat to disease prevention, control and
information management. This research therefore uses an Information Technology approach to improve the process achieving over 90% time
gain. The Gambaga Health Centre in the East Mamprusi District was selected for the simulation
Significant Role of Statistics in Computational SciencesEditor IJCATR
This paper is focused on the issues related to optimizing statistical approaches in the emerging fields of Computer Science
and Information Technology. More emphasis has been given on the role of statistical techniques in modern data mining. Statistics is
the science of learning from data and of measuring, controlling, and communicating uncertainty. Statistical approaches can play a vital
role for providing significance contribution in the field of software engineering, neural network, data mining, bioinformatics and other
allied fields. Statistical techniques not only helps make scientific models but it quantifies the reliability, reproducibility and general
uncertainty associated with these models. In the current scenario, large amount of data is automatically recorded with computers and
managed with the data base management systems (DBMS) for storage and fast retrieval purpose. The practice of examining large preexisting
databases in order to generate new information is known as data mining. Presently, data mining has attracted substantial
attention in the research and commercial arena which involves applications of a variety of statistical techniques. Twenty years ago
mostly data was collected manually and the data set was in simple form but in present time, there have been considerable changes in
the nature of data. Statistical techniques and computer applications can be utilized to obtain maximum information with the fewest
possible measurements to reduce the cost of data collection.
KOSPEN: Challenges in empowering the communityPPPKAM
1) Non-communicable diseases (NCDs) like diabetes and hypertension are increasing in Malaysia, with over 50% of cases being undiagnosed and placing a large burden on the country's health system.
2) KOSPEN is Malaysia's community-based intervention program aimed at empowering communities to prevent and control NCDs and their risk factors. It uses health volunteers to promote healthy behaviors and screen for early detection of NCD risk factors.
3) The challenges of KOSPEN implementation include increasing community prioritization of health, motivating volunteers, and ensuring adequate support from the health sector and collaborating agencies for large-scale nationwide implementation.
Developmental milestones for postgraduate students Azad Haleem
The document discusses growth and development in children. It defines growth as a quantitative increase in size, while development refers to qualitative improvements in skills and abilities. Four developmental domains are identified: gross motor, fine motor, language, and cognitive/social skills. Assessment tools for infants and older children are listed. The summary should assess development in these key areas and note the importance of a thorough history and examination to evaluate causes of developmental delay.
Health Care Data Sets and their purpose
UHDDS, UACDS, MDS, OASIS, DEEDS and EMDS.
Explain the standardization data collection efforts.
Explain the five type of standards that need to be in place to implement the Nationwide Health Information Network (NHIN).
Standard Development Organizations
Evolving and Emerging Health Information Standards
The document discusses key concepts in health planning and management. It defines management as the process of planning, organizing, leading, and controlling organizational resources to achieve goals. It also defines the main functions of management as planning, organizing, leading, and controlling. Finally, it explains the differences between effectiveness (achieving intended results) and efficiency (achieving maximum results with minimum wasted effort or expense).
This document compares the physical geography, demography, economy, and standards of living between Spain and the Netherlands. Some key points:
- Spain has more geographic diversity than the Netherlands, with higher average elevations and mountains compared to the lower and flatter terrain in the Netherlands.
- The population of Spain is over 4 times larger than the Netherlands, though population densities are much lower in Spain. The Netherlands has the tallest people on average.
- While the Netherlands has one of the strongest economies in the world, Spain has faced economic crises with higher unemployment. Tourism is a major industry for Spain.
- Standards of living are higher in some measures in the Netherlands, such as youth independence and
The document discusses epidemiological surveillance systems. It defines surveillance as the systematic collection and analysis of health data to understand disease patterns and control diseases. The objectives of surveillance include monitoring disease trends, identifying outbreaks, and informing public health policies. Effective surveillance requires defining conditions of interest, collecting standardized data, analyzing trends over time and place, and disseminating findings to decision-makers.
The document describes a healthcare management system that will maintain medical histories of patients, employees, and dependents. It will track medicine stock and issuance using inventory management. The system requires initial entry of master data that is rarely changed. Medical histories reference this master data, and patient/dependent information is automatically retrieved using a registration number. The document outlines the process for treatment, including generating medical slips, doctor examination, prescriptions, pharmacy medicine issuance, referrals, and stock tracking. It lists reports like medical examination history, test results, lists of providers, and master data screens for areas, ailments, specialties, and more.
The document provides an overview of community and public health in the Philippines. It defines public health as ecological and multi-sectoral in scope, aiming to improve community health through organized community efforts. The history of public health in the Philippines is then traced from the pre-American occupation period to the present day, noting the establishment of early hospitals and health programs under Spanish colonial rule. Major concepts of public health like health promotion, disease prevention, and community participation are also outlined.
This is a short presentation to accompany a collection of case studies and evaluations I did while pursuing my MBA.It covers a VERY brief description and comparison of the management aspect of healthcare and healthcare sciences.
"Medical Doctors are Poor Managers". This presentation has tried to do brainstorming for them how to operate as better Health Managers. Leaders lead from the Front. Managers control from the Behind. A Doctor in a facility needs to play the role of both Leader as well as Manager.
The document summarizes the history of public health from ancient times through modern times. It discusses developments in Greece, Rome, India, China, and highlights key figures like Hippocrates and Galen in ancient times. It then covers the birth of modern public health in Europe during the Renaissance and developments in Britain that led to the sanitary awakening in the 19th century. It concludes with brief overviews of public health in British India and developments in India post-independence.
This document contains lecture notes on Health Service Management for second year public health students. It covers the following topics over two lecture days:
Day 1 topics include definitions of management and health management, the historical development of management, the differences between management and administration, management functions including planning, organizing, staffing, directing, and controlling.
Day 2 topics include management and the external environment, the roles and types of managers including first line, middle, and top managers, necessary management skills at different levels, and key management concepts and principles such as effectiveness, efficiency, and management by objectives.
The document provides an overview of important concepts in health service management through detailed lecture outlines intended to educate students in this subject area.
Public Health Questions and Answers for StudentsNayyar Kazmi
This document contains definitions and explanations of key epidemiological concepts and study designs. It discusses topics such as epidemiology and its uses, the epidemiological triad, retrospective and prospective study designs, case-control and cohort studies, randomized controlled trials, sampling methods, epidemic and pandemic diseases, prevalence and incidence rates, and primary and secondary cases.
This document provides an overview of public health surveillance. It defines surveillance as the ongoing collection, analysis, and interpretation of health data to inform public health programs and actions. The document outlines the historical origins of surveillance dating back to ancient Greece. It describes various types of surveillance including community-level surveillance, routine reporting systems, active and passive surveillance, sentinel surveillance, and surveys. It also discusses the integrated disease surveillance program in India and how it aims to strengthen surveillance systems at the state and district levels.
This very short document appears to be in an unfamiliar language and does not provide much contextual information to summarize. It contains a few words that are unclear in meaning along with references to place names that are not well known out of context. The document leaves off with an ambiguous ending of "The end? To be continued".
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.
Epidemic Alert System: A Web-based Grassroots ModelIJECEIAES
This document summarizes research on web-based epidemic alert systems. It discusses how most current systems analyze large amounts of unstructured data from various online sources using complex algorithms, which can generate imprecise results given the lack of standards. The document then proposes a new grassroots web-based system that collects structured data directly from primary health centers, hospitals, and laboratories. This traditional approach uses threshold values based on percentiles to determine when an epidemic is triggered. If adopted, it could help standardize web-based disease surveillance.
This document summarizes the transition from clinical information systems to health grids and the future of health research infrastructure. It discusses trends like rising populations in Asia, increasing resource scarcity, and the need for multidisciplinary and open collaboration. Health grids are presented as enabling virtual collaborations across institutions. Key areas like medical imaging, computational models, and genomic medicine are highlighted. Adoption challenges and requirements like reliable, usable infrastructure are also summarized.
This document discusses geohealth, which combines geospatial data and digital technologies to improve public health. It addresses challenges like personalized healthcare, data-driven societies, and smart environments. Geohealth research focuses on topics like infection prevention, one health, and quantified self. Combining eHealth platforms, geospatial data, and other digital tools can help monitor health risks in real-time, predict disease outbreaks, and develop tailored interventions. The document also discusses collaborations and education initiatives around geohealth.
KOSPEN: Challenges in empowering the communityPPPKAM
1) Non-communicable diseases (NCDs) like diabetes and hypertension are increasing in Malaysia, with over 50% of cases being undiagnosed and placing a large burden on the country's health system.
2) KOSPEN is Malaysia's community-based intervention program aimed at empowering communities to prevent and control NCDs and their risk factors. It uses health volunteers to promote healthy behaviors and screen for early detection of NCD risk factors.
3) The challenges of KOSPEN implementation include increasing community prioritization of health, motivating volunteers, and ensuring adequate support from the health sector and collaborating agencies for large-scale nationwide implementation.
Developmental milestones for postgraduate students Azad Haleem
The document discusses growth and development in children. It defines growth as a quantitative increase in size, while development refers to qualitative improvements in skills and abilities. Four developmental domains are identified: gross motor, fine motor, language, and cognitive/social skills. Assessment tools for infants and older children are listed. The summary should assess development in these key areas and note the importance of a thorough history and examination to evaluate causes of developmental delay.
Health Care Data Sets and their purpose
UHDDS, UACDS, MDS, OASIS, DEEDS and EMDS.
Explain the standardization data collection efforts.
Explain the five type of standards that need to be in place to implement the Nationwide Health Information Network (NHIN).
Standard Development Organizations
Evolving and Emerging Health Information Standards
The document discusses key concepts in health planning and management. It defines management as the process of planning, organizing, leading, and controlling organizational resources to achieve goals. It also defines the main functions of management as planning, organizing, leading, and controlling. Finally, it explains the differences between effectiveness (achieving intended results) and efficiency (achieving maximum results with minimum wasted effort or expense).
This document compares the physical geography, demography, economy, and standards of living between Spain and the Netherlands. Some key points:
- Spain has more geographic diversity than the Netherlands, with higher average elevations and mountains compared to the lower and flatter terrain in the Netherlands.
- The population of Spain is over 4 times larger than the Netherlands, though population densities are much lower in Spain. The Netherlands has the tallest people on average.
- While the Netherlands has one of the strongest economies in the world, Spain has faced economic crises with higher unemployment. Tourism is a major industry for Spain.
- Standards of living are higher in some measures in the Netherlands, such as youth independence and
The document discusses epidemiological surveillance systems. It defines surveillance as the systematic collection and analysis of health data to understand disease patterns and control diseases. The objectives of surveillance include monitoring disease trends, identifying outbreaks, and informing public health policies. Effective surveillance requires defining conditions of interest, collecting standardized data, analyzing trends over time and place, and disseminating findings to decision-makers.
The document describes a healthcare management system that will maintain medical histories of patients, employees, and dependents. It will track medicine stock and issuance using inventory management. The system requires initial entry of master data that is rarely changed. Medical histories reference this master data, and patient/dependent information is automatically retrieved using a registration number. The document outlines the process for treatment, including generating medical slips, doctor examination, prescriptions, pharmacy medicine issuance, referrals, and stock tracking. It lists reports like medical examination history, test results, lists of providers, and master data screens for areas, ailments, specialties, and more.
The document provides an overview of community and public health in the Philippines. It defines public health as ecological and multi-sectoral in scope, aiming to improve community health through organized community efforts. The history of public health in the Philippines is then traced from the pre-American occupation period to the present day, noting the establishment of early hospitals and health programs under Spanish colonial rule. Major concepts of public health like health promotion, disease prevention, and community participation are also outlined.
This is a short presentation to accompany a collection of case studies and evaluations I did while pursuing my MBA.It covers a VERY brief description and comparison of the management aspect of healthcare and healthcare sciences.
"Medical Doctors are Poor Managers". This presentation has tried to do brainstorming for them how to operate as better Health Managers. Leaders lead from the Front. Managers control from the Behind. A Doctor in a facility needs to play the role of both Leader as well as Manager.
The document summarizes the history of public health from ancient times through modern times. It discusses developments in Greece, Rome, India, China, and highlights key figures like Hippocrates and Galen in ancient times. It then covers the birth of modern public health in Europe during the Renaissance and developments in Britain that led to the sanitary awakening in the 19th century. It concludes with brief overviews of public health in British India and developments in India post-independence.
This document contains lecture notes on Health Service Management for second year public health students. It covers the following topics over two lecture days:
Day 1 topics include definitions of management and health management, the historical development of management, the differences between management and administration, management functions including planning, organizing, staffing, directing, and controlling.
Day 2 topics include management and the external environment, the roles and types of managers including first line, middle, and top managers, necessary management skills at different levels, and key management concepts and principles such as effectiveness, efficiency, and management by objectives.
The document provides an overview of important concepts in health service management through detailed lecture outlines intended to educate students in this subject area.
Public Health Questions and Answers for StudentsNayyar Kazmi
This document contains definitions and explanations of key epidemiological concepts and study designs. It discusses topics such as epidemiology and its uses, the epidemiological triad, retrospective and prospective study designs, case-control and cohort studies, randomized controlled trials, sampling methods, epidemic and pandemic diseases, prevalence and incidence rates, and primary and secondary cases.
This document provides an overview of public health surveillance. It defines surveillance as the ongoing collection, analysis, and interpretation of health data to inform public health programs and actions. The document outlines the historical origins of surveillance dating back to ancient Greece. It describes various types of surveillance including community-level surveillance, routine reporting systems, active and passive surveillance, sentinel surveillance, and surveys. It also discusses the integrated disease surveillance program in India and how it aims to strengthen surveillance systems at the state and district levels.
This very short document appears to be in an unfamiliar language and does not provide much contextual information to summarize. It contains a few words that are unclear in meaning along with references to place names that are not well known out of context. The document leaves off with an ambiguous ending of "The end? To be continued".
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.
Epidemic Alert System: A Web-based Grassroots ModelIJECEIAES
This document summarizes research on web-based epidemic alert systems. It discusses how most current systems analyze large amounts of unstructured data from various online sources using complex algorithms, which can generate imprecise results given the lack of standards. The document then proposes a new grassroots web-based system that collects structured data directly from primary health centers, hospitals, and laboratories. This traditional approach uses threshold values based on percentiles to determine when an epidemic is triggered. If adopted, it could help standardize web-based disease surveillance.
This document summarizes the transition from clinical information systems to health grids and the future of health research infrastructure. It discusses trends like rising populations in Asia, increasing resource scarcity, and the need for multidisciplinary and open collaboration. Health grids are presented as enabling virtual collaborations across institutions. Key areas like medical imaging, computational models, and genomic medicine are highlighted. Adoption challenges and requirements like reliable, usable infrastructure are also summarized.
This document discusses geohealth, which combines geospatial data and digital technologies to improve public health. It addresses challenges like personalized healthcare, data-driven societies, and smart environments. Geohealth research focuses on topics like infection prevention, one health, and quantified self. Combining eHealth platforms, geospatial data, and other digital tools can help monitor health risks in real-time, predict disease outbreaks, and develop tailored interventions. The document also discusses collaborations and education initiatives around geohealth.
This document discusses geohealth, which combines geospatial data and digital technologies to improve public health. It addresses challenges like personalized healthcare, data-driven societies, and smart environments. Geohealth research focuses on topics like infection prevention, one health, and quantified self. Combining eHealth platforms, geospatial data, and other digital tools can help monitor health risks in real-time and tailor interventions. Collaboration across different fields and countries is needed to further geohealth research and applications. The goal is to use new technologies and data to more effectively ensure safety, health, and well-being.
An Overview on the Use of Data Mining and Linguistics Techniques for Building...ijcsit
The usage of Online Social Networks (OSN), such as Facebook and Twitter are becoming more and more
popular in order to exchange and disseminate news and information in real-time. Twitter in particular
allows the instant dissemination of short messages in the form of microblogs to followers. This Survey
reviews literature to explore and examine the usage of how OSNs, such as the microblogging tool Twitter,
can help in the detection of spreading epidemics. The paper highlights significant challenges in the field of
Natural Language Processing (NLP) when using microblog based Early Disease Detection Systems. For
instance, microblogging data is an unstructured collection of short messages (140 characters in Twitter),
with noise and non-standard use of the English language. Hence, research is currently exploring the field
of linguistics in order to determine the semantics of the text and uses data mining techniques in order to
extract useful information for disease spread detection. Furthermore, the survey discusses applications and
existing early disease detection systems based on OSNs and outlines directions for future research on
improving such systems based on a combination of linguistics methods, data mining techniques and
recommendation systems.
Machine learning approaches in the diagnosis of infectious diseases-a review.pdfSmriti Mishra
This document reviews machine learning approaches for diagnosing infectious diseases. It discusses how machine learning algorithms like logistic regression, K-nearest neighbors, support vector machines, decision trees, naive Bayes, neural networks, and ensemble techniques have been applied to diagnose diseases like tuberculosis, influenza, HIV, dengue fever, COVID-19, cystitis, and nonspecific urethritis. Existing models have limitations related to data quality and availability. Ensemble approaches that combine multiple models may improve performance over single classifiers. Developing models requires diverse, high-quality data that accurately represents reality.
Supporting epidemic intelligence, personalised and public health with advance...Joao Pita Costa
Today, our everyday access to technology permits a health monitoring that can complement the traditional methods in Healthcare and Public Health. In this paper, we present some of this available technology, with a particular focus on disease detection, topological data analysis, and media monitoring tools, made available by the AILAB at the JSI and the ISI Foundation. This technology is ready to be adapted to research and commercial problems in the context of health systems.
Researchers are developing an interactive system called an eXperience Induction Machine (XIM) that uses virtual reality to help users efficiently make sense of large and complex datasets. The XIM monitors a user's physical reactions as they examine data and constantly adapts the data presentation in real-time to prevent brain overload and guide the user's exploration. Several museums and universities have expressed interest in using the technology to help students learn more efficiently or allow researchers to gain new insights from large datasets. The EU-funded CEEDs project involves 16 partners across Europe working to optimize human understanding of big data through tools like the XIM.
Invited talk "Open Data as a driver of Society 5.0: how you and your scientif...Anastasija Nikiforova
This presentation is prepared as a part of my talk on the openness (open data and open science) in the context of Society 5.0 during the International Conference and Expo on Nanotechnology and Nanomaterials. It was very pleasant to receive an invitation to deliver the talk on my recently published article Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough? (Sensors 2021, 21(15), 5204), which I have entitled as “Open Data as a driver of Society 5.0: how you and your scientific outputs can contribute to the development of the Super Smart Society and transformation into Smart Living?“. The paper has been briefly discussed in my previous post, thus, just a few words on this talk and overall experience.
Dr. Nigel Collier presented on using natural language processing for mining online health-related data from social media. He discussed several case studies that demonstrated how social media data can be used for infectious disease monitoring, drug safety analysis, and analyzing the effects of exercise on mental health. However, he noted that ambiguity is a key challenge for natural language processing of social media data.
Will Yu of Lumiata provides an overview of using real-time big analytics with ever-learning graph combining hundreds of healthcare data sets. Presented at YTH Live 2014 plenary session "Mapping Big Data, Infographics and other Good Stuff."
Monitoring Indonesian online news for COVID-19 event detection using deep le...IJECEIAES
Even though coronavirus disease 2019 (COVID-19) vaccination has been done, preparedness for the possibility of the next outbreak wave is still needed with new mutations and virus variants. A near real-time surveillance system is required to provide the stakeholders, especially the public, to act in a timely response. Due to the hierarchical structure, epidemic reporting is usually slow particularly when passing jurisdictional borders. This condition could lead to time gaps for public awareness of new and emerging events of infectious diseases. Online news is a potential source for COVID-19 monitoring because it reports almost every infectious disease incident globally. However, the news does not report only about COVID-19 events, but also various information related to COVID-19 topics such as the economic impact, health tips, and others. We developed a framework for online news monitoring and applied sentence classification for news titles using deep learning to distinguish between COVID-19 events and non-event news. The classification results showed that the fine-tuned bidirectional encoder representations from transformers (BERT) trained with Bahasa Indonesia achieved the highest performance (accuracy: 95.16%, precision: 94.71%, recall: 94.32%, F1-score: 94.51%). Interestingly, our framework was able to identify news that reports the new COVID strain from the United Kingdom (UK) as an event news, 13 days before the Indonesian officials closed the border for foreigners.
OII Summer Doctoral Programme 2010: Global brain by Meyer & SchroederEric Meyer
The document discusses how technology is driving research to become more collaborative globally through distributed and networked tools. It examines several case studies where technologies enabled large-scale collaborative research projects that addressed questions too big for individual labs. These include distributed computing for particle physics, genomic studies, and proteomics. Challenges discussed include interoperability, data sharing policies, and sustaining momentum in infrastructure.
ECDC and early detection of public health threats of EU concern: the role of ...Global Risk Forum GRFDavos
The document summarizes the role of the European Centre for Disease Prevention and Control (ECDC) in early detection of public health threats in the European Union. The ECDC uses an epidemic intelligence system to collect and analyze information from various sources, including media reports, to rapidly detect potential health threats. In 2009, 39% of threats followed by ECDC were first identified through unofficial web-based information like early warning systems and media reports. The document questions what the public health impact is of early detection through media and informal channels.
Facebook: An Innovative Influenza Pandemic Early Warning SystemChen Luo
Facebook could be used as an innovative system to track influenza pandemics through a social media application. The application would simplify symptom tracking and use Facebook's viral sharing features to rapidly increase participation worldwide. During initial beta testing, over 70% of participants filled out weekly symptom questionnaires. Location data from IP addresses could provide real-time global surveillance of influenza spread. Widespread adoption of the application is now sought to validate its effectiveness as an early warning system.
Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infe...Flávio Codeço Coelho
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This curriculum vitae summarizes Nicola Amoroso's education and professional experience. He holds a PhD in Physics from 2014 with a thesis on quantitative MRI analysis in Alzheimer's disease. His postdoctoral research has focused on developing cloud computing solutions to support neuroimaging data analysis. He has published over 10 papers in peer-reviewed journals on topics including hippocampal segmentation, machine learning applications for brain disease detection, and complex network analysis of neuroimaging data.
Using eHealth to manage chronic diseases in a person-centred approach to carelikewildfire
A multidisciplinary reflexion on health issues of the 21st century could lead to innovative solutions. One of the challenges to overcome in the coming decades is how to support the increasing number of chronic patients in a pressured healthcare ecology. Patients in chronic disease management are expected to increasingly use Information and Communication Technology (ICT) for self-care during their treatment process and for co-decision with health care providers. The application of these types of information and communication technology is looked upon as one of the ways to get both patients and healthcare providers more involved in their treatment and to increase the health related quality of care, according to the WHO. Connecting patients and health care professionals would not only improve the technical system of communicating but also triggers social innovations of care models in which new ways of interacting and deciding improves the diagnostics and treatment. So far, a general overview of the extent and nature of published research involving this subset of ICT-interventions is lacking. Based on a scoping review conducted by Wildevuur e.o cancer was chosen as a case study to research how ICT could support cancer-patients in a person-centred approach to care.
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Dr. Edward Velasco - “Intelligent Use” of Electronic Data to Enhance Public Health Surveillance
1. “Intelligent Use” of Electronic Data to
Enhance Public Health Surveillance
Dr. Edward Velasco
Department of Infectious Disease Epidemiology
Robert Koch Institute (Public Health Agency of Germany)
Berlin
2. 2
~5 Days t
Event arises
Established
surveillance
systems: SurvNet,
targeted surveillance
systems (e.g.
sentinels)
3 Days
Existing event-based
services: EWRS,
government websites,
ProMed Mail, MedISys,
news
What is important from our perspective?
2 Days
Web 2.0 and
user generated
sources ?
Time needed to spot an infectious disease health event
3. M-Eco (Medical Ecosystem)
EU 7th Framework project international project,
2010-2012
Goal generate, extract, organise and present
viable information from Internet data for public
health surveillance and early warning of
infectious diseases
4. User specifications
4
1. Data is generated from the Web
in a timely and specific way
Websites: news, publications, Web 2.0 and user-
generated sources (social media, Twitter,
Facebook, blogs)
2. Data is extracted & organised
Epidemiological information is extracted and
personalised based on signal needs: time
frame, place, symptoms , etc.
3. Data is made easily available
and user-friendly
Visualisation possibilities for time and geographic
analysis
5. Data generation, extraction, organisation,
presentation
How to Exploit Twitter for Public Health Monitoring? GMDS 2012 – Medical Informatics, Medicine and Neighboring Disciplines. K. Denecke (1, 2),
M. Krieck (3), L. Otrusina (4), P. Smrz (4), P. Dolog (5), W. Nejdl (2), E. Velasco (6)
6. Innovation: Intelligent data extraction
• Media & text mining
Keyword identification, semantic trees
How to Exploit Twitter for Public Health Monitoring? GMDS 2012 – Medical Informatics, Medicine and Neighboring Disciplines. K. Denecke (1, 2),
M. Krieck (3), L. Otrusina (4), P. Smrz (4), P. Dolog (5), W. Nejdl (2), E. Velasco (6)
7. Innovation: Algorithmic automation, interactive data
presentation
How to Exploit Twitter for Public Health Monitoring? GMDS 2012 – Medical Informatics, Medicine and Neighboring Disciplines. K. Denecke (1, 2),
M. Krieck (3), L. Otrusina (4), P. Smrz (4), P. Dolog (5), W. Nejdl (2), E. Velasco (6)
Tag cloud
Signal list
Interactive epicurve/timeline
8. Evaluation 1: How well does the system
generate signals?
General simulation with Twitter
13 scientists created tweets for mock scenarios:
– A. Measles in a school
– B. Salmonella at Eurocup
– C. Hepatitis A: returning travellers
Tweets were fed into M-Eco, mixed with real-world tweets and
analysed
Only 1/3 became part of signal (21%): this is low! 75-80% expected
– Keywords not comprehensive enough: slang does not equal
medical terms in our keywords lists
– Geolocation is difficult to aggregate, missing information
– German language?
9. Evaluation 2: How does the system perform in
real time?
Real signal production during mass gathering: Euro 2012,
men‘s football championship, Poland/Ukraine
Signals provided to „subscribers“ at RKI and NLGA
– Daily monitoring alongside regular work
20 signals avg/day; 242 signals total
– 13 total relevant over the event-time: this is low!
Again: Problems with keywords/terms: slang or off-use of terms
„football fever“ „weakness“ of players“ or „headache“ from poor
performance
10. Evaluation 3: Signal production over 3 weeks
Weekend!
Media coverage of flu-shot shortages!
11. Unresolved challenges
Information is not always moderated by professionals or
interpreted for relevance before it is disseminated to
epidemiologists, i.e. tweets, media reports
Automation: no standardized system for updates, often
resulting in too much information
Algorithms and statistical baselines are not well developed
New information about health events is not disseminated in
the most efficient way
12. Interdisciplinary challenges ahead
Social aspects
– Privacy and data protection - legal/ethical concerns over
data access?
– Artificial cognition systems
Bridging with traditional epidemiology
– Evolving stakeholder roles
– Data mining, automated systems replace people?
– Comparison to traditional surveillance data unexplored
– Big data: Unknown infrastructural investments for data
storage
12
13. 13
Thank you
Some references for your review:
Social Media and Internet-Based Data in Global Systems for Public Health Surveillance: A
Systematic Review. The Milbank Quarterly, Vol. 92, No. 1, 2014 (pp. 7-33) Velasco E,
Agheneza A, Denecke K, Kirchner G, Eckmanns T.
How to Exploit Twitter for Public Health Monitoring? Methods of Information in Medicine,
Vol. 52, No. 4, 2013 (pp. 326-339) Denecke K, Krieck M, Otrusina L, Smrz P, Dolog P, Nejdl W,
Velasco E.
Website: www.meco-project.eu
Contact
Edward Velasco, PhD, SM
Department for Infectious Disease Epidemiology
Robert Koch Institute, Berlin
Email: VelascoE@rki.de
14. 14
M-Eco Project, Partners, Consortium and Advisory
FP 7th Framework EU Project, 2010-2012, website: www.meco-project.eu
Computer Science & Information Technology
– L3S Research Centre, Leibnitz University Hannover, Germany (LUH) (Partner)
– Aalborg University, Intelligent Web and Information Systems, Department of Computer Science,
Denmark (AAU) (Partner)
– SAIL Labs, Austria (SAIL) (Partner)
– Brno University of Technology, Faculty of Information Technology, Czech Republic (BUT) (Partner)
– Joint Research Centre, European Commission, Italy (JRC) (Partner)
Epidemiology and Surveillance
– State Public Health Agency of Lower Saxony, Germany (NLGA) (Partner)
– Robert Koch Institute, Department for Infectious Disease Epidemiology, Surveillance Unit,
Germany (RKI) (Partner)
– Health Protection Agency, UK, (HPA) (Advisory)
– Institut de Veille Sanitaire, France, (INVS) (Advisory)
– European Centre for Disease Prevention and Control, Stockholm, (ECDC) (Advisory)
– Global Alert and Response, World Health Organization, Switzerland, (WHO) (Advisory)