This paper is in the following e-collection/theme issue:

Digital Health Reviews (1724) Artificial Intelligence (2129) Reviews (133) Clinical Information and Decision Making (1915) Machine Learning (2076) Obesity (117) Obesity and Nutrition as Public Health Problem (397)

Published on in Vol 24, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40589, first published .
Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies

Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies

Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies

Authors of this article:

Ruopeng An1 Author Orcid Image ;   Jing Shen2 Author Orcid Image ;   Yunyu Xiao3 Author Orcid Image
Article Authors Cited by (46) Tweetations (12) Metrics

Journals

  1. Bays H, Fitch A, Cuda S, Gonsahn-Bollie S, Rickey E, Hablutzel J, Coy R, Censani M. Artificial intelligence and obesity management: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2023. Obesity Pillars 2023;6:100065 View
  2. An R, Ji M. Building Machine Learning Models to Correct Self-Reported Anthropometric Measures. Journal of Public Health Management & Practice 2023;29(5):671 View
  3. Aiosa G, Palesi M, Sapuppo F. EXplainable AI for Decision Support to Obesity Comorbidities Diagnosis. IEEE Access 2023;11:107767 View
  4. An R, Batcheller Q, Wang J, Yang Y. Build neural network models to identify and correct news headlines exaggerating obesity-related scientific findings. Journal of Data and Information Science 2023;8(3):88 View
  5. Knights V, Kolak M, Markovikj G, Kljusurić J. Modeling and Optimization with Artificial Intelligence in Nutrition. Applied Sciences 2023;13(13):7835 View
  6. Visco V, Izzo C, Bonadies D, Di Feo F, Caliendo G, Loria F, Mancusi C, Chivasso P, Di Pietro P, Virtuoso N, Carrizzo A, Vecchione C, Ciccarelli M. Interventions to Address Cardiovascular Risk in Obese Patients: Many Hands Make Light Work. Journal of Cardiovascular Development and Disease 2023;10(8):327 View
  7. Lippi L, de Sire A, Folli A, Turco A, Moalli S, Marcasciano M, Ammendolia A, Invernizzi M. Obesity and Cancer Rehabilitation for Functional Recovery and Quality of Life in Breast Cancer Survivors: A Comprehensive Review. Cancers 2024;16(3):521 View
  8. Trinkley K, An R, Maw A, Glasgow R, Brownson R. Leveraging artificial intelligence to advance implementation science: potential opportunities and cautions. Implementation Science 2024;19(1) View
  9. Nashwan A, Abdi Hassan M, AlBarakat M. Rethinking BMI and Obesity Management: The Transformative Role of Artificial Intelligence. Cureus 2024 View
  10. Huang J, Guo P, Zhang S, Ji M, An R. Use of Deep Neural Networks to Predict Obesity With Short Audio Recordings: Development and Usability Study. JMIR AI 2024;3:e54885 View
  11. Danilov S, Matveev G, Babenko A, Shlyakhto E. Model for Predicting the Effect of Sibutramine Therapy in Obesity. Journal of Personalized Medicine 2024;14(8):811 View
  12. Nashruddin S, Salleh F, Yunus R, Zaman H. Artificial intelligence−powered electrochemical sensor: Recent advances, challenges, and prospects. Heliyon 2024;10(18):e37964 View
  13. Ramos-Jiménez A, Hernández Lepe M, Hernández-Torres R, Murguía-Romero M. Heuristic evaluation of body mass index with bioimpedance data in the Mexican population. Nutrición Hospitalaria 2024 View
  14. Gong X, Bai S, Lei E, Lin L, Chen Y, Liu J. Study of obesity research using machine learning methods: A bibliometric and visualization analysis from 2004 to 2023. Medicine 2024;103(36):e39610 View
  15. Kim D, Park C, Shin J, Lee H. The Role of Artificial Intelligence in Obesity Medicine. Endocrinology and Metabolism Clinics of North America 2025;54(1):207 View
  16. Kim S. Trends and Perspectives of mHealth in Obesity Control. Applied Sciences 2024;15(1):74 View
  17. Liu X, Susarla A, Padman R. Promoting Health Literacy With Human-in-the-Loop Video Understandability Classification of YouTube Videos: Development and Evaluation Study. Journal of Medical Internet Research 2025;27:e56080 View
  18. Magan D, Yadav R, Aneja J, Pandey S. Association Between BMI and Neurocognitive Functions Among Middle-aged Obese Adults: Preliminary Findings Using Machine-learning (ML)-based Approach. Annals of Neurosciences 2025 View
  19. Azmi S, Kunnathodi F, Alotaibi H, Alhazzani W, Mustafa M, Ahmad I, Anvarbatcha R, Lytras M, Arafat A. Harnessing Artificial Intelligence in Obesity Research and Management: A Comprehensive Review. Diagnostics 2025;15(3):396 View
  20. Park J, Park S, Lee K, Kwon Y. Predictive and Explainable Artificial Intelligence for Weight Loss After Sleeve Gastrectomy: Insights from Wide and Deep Learning with Medical Image and Non-Image Data. Applied Sciences 2025;15(5):2457 View
  21. Flølo T, Tørris C, Riiser K, Almendingen K, Chew H, Fosså A, Albertini Früh E, Hennessy E, Leung M, Misvær N, Pavel N, Sundar T, Sæterstrand T, Torbjørnsen A, Løyland B, Holmen H. Digital health interventions to treat overweight and obesity in children and adolescents: An umbrella review. Obesity Reviews 2025;26(6) View
  22. Choong C, Xavier N, Falcon B, Kan H, Lipkovich I, Nowak C, Hoyt M, Houle C, Kahan S. Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States. Diabetes, Obesity and Metabolism 2025;27(6):3061 View
  23. Meder B, Asselbergs F, Ashley E. Artificial intelligence to improve cardiovascular population health. European Heart Journal 2025;46(20):1907 View
  24. Boakye N, O'Toole C, Jalali A, Hannigan A. Comparing logistic regression and machine learning for obesity risk prediction: A systematic review and meta-analysis. International Journal of Medical Informatics 2025;199:105887 View
  25. Zheng M, Zhang Y, Laws R, Vuillermin P, Dodd J, Wen L, Baur L, Taylor R, Byrne R, Ponsonby A, Hesketh K. Development of Machine Learning–Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts. JMIR Public Health and Surveillance 2025;11:e69220 View
  26. Awari A, Kaushik D, Kumar A, Oz E, Çadırcı K, Brennan C, Proestos C, Kumar M, Oz F. Obesity Biomarkers: Exploring Factors, Ramification, Machine Learning, and AI‐Unveiling Insights in Health Research. MedComm 2025;6(7) View
  27. Carrillo-Larco R. Classification of body mass index levels using breast thermography: A preliminary proof-of-concept analysis with convolutional neural networks. Smart Health 2025;37:100597 View
  28. Naumova E, Hsieh A, Ran‐Ressler R, Jang C, Huey S, Dionisi F. Application of Artificial Intelligence to Lipid Nutrition: A Narrative Review. Lipids 2025;60(6):459 View
  29. Sun Z, Zhang R, Cong M, Zhang M, Lv T, Xie H, Chen S. Global burden of hypertensive heart disease attributable to high body mass index from 1990 to 2021: a multidimensional analysis and public health response. Frontiers in Cardiovascular Medicine 2025;12 View
  30. Wang F, Wang L, Zhong L, Feng J, Wang X. Artificial Intelligence for Knee Osteoarthritis Care and Rehabilitation: A Systematic Review. Pain Management Nursing 2025 View
  31. Yáñez-Sepúlveda R, Vásquez-Bonilla A, Olivares R, Olivares P, Zavala-Crichton J, Hinojosa-Torres C, Muñoz-Strale C, Giakoni-Ramírez F, de Souza-Lima J, Páez-Herrera J, Olivares-Arancibia J, Reyes-Amigo T, Cortés-Roco G, Hurtado-Almonacid J, Guzmán-Muñoz E, Aguilera-Martínez N, López-Gil J, Becerra-Patiño B, Paucar-Uribe J, Garcia-Carrillo E, Clemente-Suárez V. Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis. Scientific Reports 2025;15(1) View
  32. Anker S, Ji L, Kindel T, Coats A, Ojji D, Puente Barragán A, Rossing P, Zieroth S, Ahmad S, Usman S, Appannah G, Bailey A, Bennis A, Brandao A, Butler J, Davies M, Fabryova L, Guo Y, Itoh H, Jadhav U, Le Roux C, Pinto F, Rosenstock J, Saboo B, Sabbour H, Tiwaskar M, Watson K, Tham K, Wyss Quintana F, Abhayaratna W, Abraham W, Al Mahmeed W, Argirò A, Atherton J, Belardo D, Campuzano Ruiz R, Chatterjee N, Chopra V, Cornier M, Davies S, De Rueda Panadero C, Dzudie A, Gluckman T, Shahzeb Khan M, Khunti K, Lopatin Y, Ma Z, Ogah O, Oomman A, Peralta Lopez E, Li P, Poirier P, Redfern J, Rosano G, Ryan D, Saraf A, Shaheen S, Verma S, Von Haehling S, Zhang Y, Gulati M, Sattar N, Zamorano J. iCARDIO Alliance Global Implementation Guidelines for the Management of Obesity 2025 - Focus on prevention and treatment of cardiometabolic disease. Global Cardiology 2025;3(3) View
  33. Andrade‐Calle R, de la Torre‐Díez I, de Luis‐Román D. Predictive Modeling of Weight Loss and Metabolic Health Outcomes: A Retrospective Predictive Modeling Study. Health Science Reports 2025;8(10) View
  34. Ghosh S, Bhaskar R, Singh K, Yarlagadda B, Verma P, Han S, Purohit S, Sinha J, Yasin N. Neuroprotective Potential of Free Radical‐Scavenging Nanoparticles in Addressing Inflammation and Obesity. IET Nanobiotechnology 2025;2025(1) View
  35. Hendy A, Ibrahim R, Abdelaliem S, Sultan H, Sinnokrot S, Al-Ma’ani M, Alzahrani B, Ali W, Alshammari A, Hendy A. Prediction of child nutritional status using deep neural networks: A cross-sectional study of Egypt DHS data (2005–2014). Medicine 2025;104(47):e46089 View
  36. Srivastava A, Swami K, Sharma D, Hiremath D, Srivastava K, Sharma S. Obesity: A growing health challenge, assessment, and corrective measures. Journal of Drug Research in Ayurvedic Sciences 2025;10(Suppl 2):S129 View

Books/Policy Documents

  1. Htet A, Liana S, Aung T, Bhaumik A. Advanced Applications of Generative AI and Natural Language Processing Models. View
  2. Viola Lee K, Gandhi B, Tangsrivimol J, Hassan Virk H, ElSherbini A, Wang Z, Glicksberg B, Krittanawong C. The Digital Doctor. View
  3. Canio F, Martina P, Paola D, Massimo C. Reference Module in Food Science. View
  4. Rashmi R, Snekhalatha U. Artificial Intelligence over Infrared Images for Medical Applications. View

Conference Proceedings

  1. Aiosa G, Palesi M, Sapuppo F, Xibilia M. 2023 IEEE 19th International Conference on e-Science (e-Science). Explainable AI-Based Clinical Decision Support System for Obesity Comorbidity Analysis View
  2. Vemulapalli G, Yalamati S, Palakurti N, Alam N, Samayamantri S, Whig P. 2024 Asia Pacific Conference on Innovation in Technology (APCIT). Predicting Obesity Trends Using Machine Learning from Big Data Analytics Approach View
  3. Tripathi A, Chauhan N, Sharma A. 4TH INTERNATIONAL CONFERENCE ON INNOVATION IN IOT, ROBOTICS AND AUTOMATION (IIRA 4.0). Obesity classification and prognosis using machine learning View
  4. Sharma S, Aldmour R, Glover W, Kelter M. Global Congress on Emerging Technologies (GCET-2024). Mindful Eating and Impact of Physical Activity on Weight Management using Mobile Application View
  5. V V R M, N S, Kurada R, Devi K, Priya M, Reddy S. 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES). A Robust Multi-Class Obesity Classification and Risk Analysis System by Leveraging the Potentiality of Machine Learning Techniques View
  6. N S, V V R M, Neelima B, Swain S, Raju D, N A. 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES). Optimizing Multiclass Classification for Obesity Type Prediction Using Robust Machine Learning and Feature Selection to Enhance Healthcare View