Edwin Chi Ho Lau, Vije Kumar Rajput, Inga Hunter, Jose F Florez-Arango, Prasad Ranatunga, Klaus D Veil, Gumindu Kulatunga, Shashi Gogia, Craig Kuziemsky, Marcia Ito, Usman Iqbal, Sheila John, Sriram Iyengar, Anandhi Ramachandran, Arindam Basu
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It aims to tailor preventive measures according to each individual's unique characteristics, such as genomic data, socio-demographic features, environmental factors, and cultural background.</p><p><strong>Methods: </strong>Healthcare information technologies, including telehealth and artificial intelligence (AI), have served as a vital catalyst in the expansion of this field in the past decade. Under this framework, real-time contemporaneous clinical data is collected via a wide range of digital health devices, such as telehealth monitors, wearables, etc., and then analyzed by AI or non-AI prediction models, which then generate preventive recommendations.</p><p><strong>Results: </strong>The utilization of telehealth technologies in the precision prevention of cardiovascular diseases (CVDs) is a very illustrative application. This paper explores these topics as well as certain limitations and unintended consequences (UICs) and outlines telehealth as a core enabler of precision prevention as well as public health.</p>","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"33 1","pages":"64-69"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020635/pdf/","citationCount":"0","resultStr":"{\"title\":\"Telehealth and Precision Prevention: Bridging the Gap for Individualised Health Strategies.\",\"authors\":\"Edwin Chi Ho Lau, Vije Kumar Rajput, Inga Hunter, Jose F Florez-Arango, Prasad Ranatunga, Klaus D Veil, Gumindu Kulatunga, Shashi Gogia, Craig Kuziemsky, Marcia Ito, Usman Iqbal, Sheila John, Sriram Iyengar, Anandhi Ramachandran, Arindam Basu\",\"doi\":\"10.1055/s-0044-1800720\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Precision prevention has shown an upsurge in popularity among epidemiologists in both developed and developing countries in the past decade.</p><p><strong>Objectives: </strong>Initially practiced in oncology, this approach is increasingly adopted in public health to guard against other common non-communicable diseases (NCDs), such as diabetes and cardiovascular diseases. 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Telehealth and Precision Prevention: Bridging the Gap for Individualised Health Strategies.
Introduction: Precision prevention has shown an upsurge in popularity among epidemiologists in both developed and developing countries in the past decade.
Objectives: Initially practiced in oncology, this approach is increasingly adopted in public health to guard against other common non-communicable diseases (NCDs), such as diabetes and cardiovascular diseases. It aims to tailor preventive measures according to each individual's unique characteristics, such as genomic data, socio-demographic features, environmental factors, and cultural background.
Methods: Healthcare information technologies, including telehealth and artificial intelligence (AI), have served as a vital catalyst in the expansion of this field in the past decade. Under this framework, real-time contemporaneous clinical data is collected via a wide range of digital health devices, such as telehealth monitors, wearables, etc., and then analyzed by AI or non-AI prediction models, which then generate preventive recommendations.
Results: The utilization of telehealth technologies in the precision prevention of cardiovascular diseases (CVDs) is a very illustrative application. This paper explores these topics as well as certain limitations and unintended consequences (UICs) and outlines telehealth as a core enabler of precision prevention as well as public health.
期刊介绍:
Published by the International Medical Informatics Association, this annual publication includes the best papers in medical informatics from around the world.