PAHFKB: A knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failure
Background and Aims Guidelines for exercise recommendations are typically designed for the population as a whole and do not account for individual differences, making it challenging to provide personalized exercise training for individuals with complex conditions. To address this issue, this study a...
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SAGE Publishing
2024-11-01
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| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076241299083 |
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| author | Ke Zhang Shumin Ren Ting Bao Rongrong Wu Erman Wu Xingyun Liu Chaoying Zhan Jinhong Wei Li Shen Danting Li Bairong Shen |
| author_facet | Ke Zhang Shumin Ren Ting Bao Rongrong Wu Erman Wu Xingyun Liu Chaoying Zhan Jinhong Wei Li Shen Danting Li Bairong Shen |
| author_sort | Ke Zhang |
| collection | DOAJ |
| description | Background and Aims Guidelines for exercise recommendations are typically designed for the population as a whole and do not account for individual differences, making it challenging to provide personalized exercise training for individuals with complex conditions. To address this issue, this study aimed to develop PAHFKB (Physical Activity-Heart Failure Knowledge Base), a knowledge-based system for personalized exercise prescription (EP) for heart failure (HF), by mining, analyzing, and organizing existing literature and data on the relationship between physical activity (PA) and HF. Methods Firstly, 3186 citations on PAHF were gathered from PubMed. Then, the data standards for personalized PAHF were defined with the entity-relationship model. Following data collection in accordance with these standards, PAHFKB was developed using MySQL and ASP.NET, integrating elaborate and diverse PAHF evidence, knowledge-based EP and visualization tools. Results PAHFKB (pahfkb.sysbio.org.cn) incorporated 357 studies published between 1989 and 2021, involving over 900,000 subjects from 43 countries. And 1010 PAHF items were extracted, encompassing 357 exercise training protocols, 333 outcomes, and 42 risk factors for HF prevention and intervention. Among all protocols, the most frequently employed regimen consisted of three 60-minute sessions of moderate-intensity aerobic exercise training on a weekly basis. Conclusion PAHFKB is an online system designed to support personalized EP in HF management. It incorporates diverse tools and visualization and will promote personalized decision support, establish data standards, and advance interpretable artificial intelligence in digital health. Ultimately, it will enhance clinical practice and digital therapy in the prevention and intervention of HF. |
| format | Article |
| id | doaj-art-dc5b6bb9b0524cf28d28dd697e083cfd |
| institution | Kabale University |
| issn | 2055-2076 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Digital Health |
| spelling | doaj-art-dc5b6bb9b0524cf28d28dd697e083cfd2024-11-20T10:03:30ZengSAGE PublishingDigital Health2055-20762024-11-011010.1177/20552076241299083PAHFKB: A knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failureKe Zhang0Shumin Ren1Ting Bao2Rongrong Wu3Erman Wu4Xingyun Liu5Chaoying Zhan6Jinhong Wei7Li Shen8Danting Li9Bairong Shen10 Translational Informatics Center, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , Chengdu, China Translational Informatics Center, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , Chengdu, China Health Management Center, , Chengdu, China Translational Informatics Center, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , Chengdu, China Translational Informatics Center, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , Chengdu, China Translational Informatics Center, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , Chengdu, China Translational Informatics Center, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , Chengdu, China School of Basic Medical Sciences, , Luzhou, China Translational Informatics Center, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , Chengdu, China Health Management Center, , Chengdu, China Translational Informatics Center, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , Chengdu, ChinaBackground and Aims Guidelines for exercise recommendations are typically designed for the population as a whole and do not account for individual differences, making it challenging to provide personalized exercise training for individuals with complex conditions. To address this issue, this study aimed to develop PAHFKB (Physical Activity-Heart Failure Knowledge Base), a knowledge-based system for personalized exercise prescription (EP) for heart failure (HF), by mining, analyzing, and organizing existing literature and data on the relationship between physical activity (PA) and HF. Methods Firstly, 3186 citations on PAHF were gathered from PubMed. Then, the data standards for personalized PAHF were defined with the entity-relationship model. Following data collection in accordance with these standards, PAHFKB was developed using MySQL and ASP.NET, integrating elaborate and diverse PAHF evidence, knowledge-based EP and visualization tools. Results PAHFKB (pahfkb.sysbio.org.cn) incorporated 357 studies published between 1989 and 2021, involving over 900,000 subjects from 43 countries. And 1010 PAHF items were extracted, encompassing 357 exercise training protocols, 333 outcomes, and 42 risk factors for HF prevention and intervention. Among all protocols, the most frequently employed regimen consisted of three 60-minute sessions of moderate-intensity aerobic exercise training on a weekly basis. Conclusion PAHFKB is an online system designed to support personalized EP in HF management. It incorporates diverse tools and visualization and will promote personalized decision support, establish data standards, and advance interpretable artificial intelligence in digital health. Ultimately, it will enhance clinical practice and digital therapy in the prevention and intervention of HF.https://doi.org/10.1177/20552076241299083 |
| spellingShingle | Ke Zhang Shumin Ren Ting Bao Rongrong Wu Erman Wu Xingyun Liu Chaoying Zhan Jinhong Wei Li Shen Danting Li Bairong Shen PAHFKB: A knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failure Digital Health |
| title | PAHFKB: A knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failure |
| title_full | PAHFKB: A knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failure |
| title_fullStr | PAHFKB: A knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failure |
| title_full_unstemmed | PAHFKB: A knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failure |
| title_short | PAHFKB: A knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failure |
| title_sort | pahfkb a knowledge base to support personalized exercise prescription recommendations in prevention and intervention of heart failure |
| url | https://doi.org/10.1177/20552076241299083 |
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