Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence.
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| Title: | Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence. |
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| Authors: | Görmez Y; Department of Management Information Systems, Faculty of Economics and Administrative Sciences, Sivas Cumhuriyet University, Sivas, Türkiye., Yagin FH; Department of Biostatistics, Faculty of Medicine, Malatya Turgut Ozal University, Malatya, Türkiye., Yagin B; Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya, Türkiye., Aygun Y; Department of Sport Management, Faculty of Sport Sciences, Inonu University, Malatya, Türkiye., Boke H; Yasar Oncan Secondary School, Ministry of National Education, Malatya, Türkiye., Badicu G; Department of Physical Education and Special Motricity, Faculty of Physical Education and Mountain Sports, Transilvania University of Braşov, Braşov, Romania., De Sousa Fernandes MS; Keizo Asami Institute, Federal University of Pernambuco (UFPE), Recife, Brazil., Alkhateeb A; Department of Computer Science, Lakehead University, Thunder Bay, Canada., Al-Rawi MBA; Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia., Aghaei M; Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU), Alesund, Norway.; Department of Sustainable Systems Engineering (INATECH), Albert Ludwigs University of Freiburg, Freiburg, Germany. |
| Source: | Frontiers in physiology [Front Physiol] 2025 Jul 16; Vol. 16, pp. 1549306. Date of Electronic Publication: 2025 Jul 16 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101549006 Publication Model: eCollection Cited Medium: Print ISSN: 1664-042X (Print) Linking ISSN: 1664042X NLM ISO Abbreviation: Front Physiol Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1664-042X |
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| DOI: | 10.3389/fphys.2025.1549306 |
