Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review
Self-awareness and self-management in diabetes are critical as they enhance patient well-being, decrease financial burden, and alleviate strain on healthcare systems by mitigating complications and promoting healthier life expectancy. Incomplete understanding persists regarding the synergistic effec...
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2025-02-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-2568.pdf |
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| author | Rizwan Riaz Mir Nazeef Ul Haq Kashif Ishaq Nurhizam Safie Abdul Basit Dogar |
| author_facet | Rizwan Riaz Mir Nazeef Ul Haq Kashif Ishaq Nurhizam Safie Abdul Basit Dogar |
| author_sort | Rizwan Riaz Mir |
| collection | DOAJ |
| description | Self-awareness and self-management in diabetes are critical as they enhance patient well-being, decrease financial burden, and alleviate strain on healthcare systems by mitigating complications and promoting healthier life expectancy. Incomplete understanding persists regarding the synergistic effects of diet and exercise on diabetes management, as existing research often isolates these factors, creating a knowledge gap in comprehending their combined influence. Current diabetes research overlooks the interplay between diet and exercise in self-management. A holistic study is crucial to mitigate complications and healthcare burdens effectively. Multi-dimensional research questions covering complete diabetic management such as publication channels for diabetic research, existing machine learning solutions, physical activity tacking existing methods, and diabetic-associated datasets are included in this research. In this study, using a proper research protocol primary research articles related to diet, exercise, datasets, and blood analysis are selected and their quality is assessed for diabetic management. This study interrelates two major dimensions of diabetes management together that are diet and exercise. |
| format | Article |
| id | doaj-art-df374cd5850c48529306f6d606a364d4 |
| institution | Kabale University |
| issn | 2376-5992 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj-art-df374cd5850c48529306f6d606a364d42025-02-05T15:05:07ZengPeerJ Inc.PeerJ Computer Science2376-59922025-02-0111e256810.7717/peerj-cs.2568Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature reviewRizwan Riaz Mir0Nazeef Ul Haq1Kashif Ishaq2Nurhizam Safie3Abdul Basit Dogar4Department of Computer Science and IT, Virtual University of Pakistan, Lahore, PakistanDepartment of Computer Science, University of Engineering and Technology Lahore, Lahore, PakistanSchool of Systems and Technology, University of Management & Technology, Lahore, PakistanFaculty of Information Science and Technology, Universiti Kebangsaan Malaysia, MalaysiaSchool of Systems and Technology, University of Management & Technology, Lahore, PakistanSelf-awareness and self-management in diabetes are critical as they enhance patient well-being, decrease financial burden, and alleviate strain on healthcare systems by mitigating complications and promoting healthier life expectancy. Incomplete understanding persists regarding the synergistic effects of diet and exercise on diabetes management, as existing research often isolates these factors, creating a knowledge gap in comprehending their combined influence. Current diabetes research overlooks the interplay between diet and exercise in self-management. A holistic study is crucial to mitigate complications and healthcare burdens effectively. Multi-dimensional research questions covering complete diabetic management such as publication channels for diabetic research, existing machine learning solutions, physical activity tacking existing methods, and diabetic-associated datasets are included in this research. In this study, using a proper research protocol primary research articles related to diet, exercise, datasets, and blood analysis are selected and their quality is assessed for diabetic management. This study interrelates two major dimensions of diabetes management together that are diet and exercise.https://peerj.com/articles/cs-2568.pdfDiabetes self-managementDietExerciseMachine learning |
| spellingShingle | Rizwan Riaz Mir Nazeef Ul Haq Kashif Ishaq Nurhizam Safie Abdul Basit Dogar Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review PeerJ Computer Science Diabetes self-management Diet Exercise Machine learning |
| title | Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review |
| title_full | Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review |
| title_fullStr | Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review |
| title_full_unstemmed | Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review |
| title_short | Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review |
| title_sort | impact of machine learning on dietary and exercise behaviors in type 2 diabetes self management a systematic literature review |
| topic | Diabetes self-management Diet Exercise Machine learning |
| url | https://peerj.com/articles/cs-2568.pdf |
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