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[2]. "World Health Organization Obesity and Overweight," https://www.who.int/news/item/04-03-2022-world-obesity-day-2022-accelerating-action-to-stop-obesity, 2022.
[3]. A. A. K. Kolahi et al., A. Moghisi, Y. S. Ekhtiari, "Socio-demographic determinants of obesity indexes in Iran: findings from a nationwide steps survey," 2018.
[4]. U. G. G. M. Tremmel, P. M. Nilsson, S. Saha, "Economic burden of obesity: a systematic literature review," International Journal of Environmental Research and Public Health, 2017.
[5]. D. Albuquerque, C. Nóbrega, L. Manco, and C. Padez, "The contribution of genetics and environment to obesity," British medical bulletin, vol. 123, no. 1, pp. 159-173, 2017.
[6]. K. Gawlik, Zwierzchowska, A., & Celebańska, D. (2018). Impact of physical activity on "Impact of physical activity on obesity and lipid profile of adults with intellectual disability," Wiley Online Library, 2018.
[7]. F. Ferdowsy, K. S. A. Rahi, M. I. Jabiullah, and M. T. Habib, "A machine learning approach for obesity risk prediction," Current Research in Behavioral Sciences, vol. 2, p. 100053, 2021.
[8]. M. Safaei, E. A. Sundararajan, M. Driss, W. Boulila, and A. Shapi'i, "A systematic literature review on obesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to predict obesity," Computers in biology and medicine, vol. 136, p. 104754, 2021.
[9]. K. Sweatt, Garvey, W. T., & Martins, C., "Strengths and Limitations of BMI in the Diagnosis of Obesity: What is the Path Forward?" Current Obesity Reports, 2024.
[10]. A. Triantafyllidis et al., "Computerized decision support and machine learning applications for the prevention and treatment of childhood obesity: A systematic review of the literature," Artificial Intelligence in Medicine, vol. 104, p. 101844, 2020.
[11]. A. R. Rahmanti et al., "SlimMe, a chatbot with artificial empathy for personal Weight Loss: system design and finding," Frontiers in Nutrition, vol. 9, p. 870775, 2022.
[12]. T. Miyazawa et al., "Artificial intelligence in food science and nutrition: a narrative review," Nutrition Reviews, vol. 80, no. 12, pp. 2288-2300, 2022.
[13]. A. Bond, K. Mccay, and S. Lal, "Artificial intelligence & clinical nutrition: What the future might have in store," Clinical Nutrition ESPEN, vol. 57, pp. 542-549, 2023.
[14]. T. P. Theodore Armand, K. A. Nfor, J.-I. Kim, and H.-C. Kim, "Applications of artificial intelligence, machine learning, and deep learning in nutrition: a systematic review," Nutrients, vol. 16, no. 7, p. 1073, 2024.
[15]. A. Sosa-Holwerda, O.-H. Park, K. Albracht-Schulte, S. Niraula, L. Thompson, and W. Oldewage-Theron, "The role of artificial intelligence in nutrition research: a scoping review," Nutrients, vol. 16, no. 13, p. 2066, 2024.
[16]. J. Zhu and G. Wang, "Artificial intelligence technology for food nutrition," vol. 15, ed.: MDPI, 2023, p. 4562.
[17]. N. Begum, A. Goyal, and S. Sharma, "Artificial Intelligence-Based Food Calories Estimation Methods in Diet Assessment Research," in Artificial Intelligence Applications in Agriculture and Food Quality Improvement: IGI Global, 2022, pp. 276-290.
[18]. M. Roy, S. Das, and A. T. Protity, "OBESEYE: Interpretable Diet Recommender for Obesity Management using Machine Learning and Explainable AI," arXiv preprint arXiv:2308.02796, 2023.
[19]. N. Varshney, N. Jadhav, K. Gupta, N. R. Mate, A. Rose, and P. Kumar, "Personalized Dietary Recommendations Using Machine Learning: A Comprehensive Review," in 2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), 2023, vol. 1: IEEE, pp. 1-6.
[20]. V. S. Voruganti, "Precision nutrition: recent advances in obesity," Physiology, vol. 38, no. 1, pp. 42-50, 2023.
[21]. D. P. Panagoulias, D. N. Sotiropoulos, and G. A. Tsihrintzis, "Towards personalized nutrition applications with nutritional biomarkers and machine learning," Advances in Assistive Technologies: Selected Papers in Honour of Professor Nikolaos G. Bourbakis – Vol. 3, pp. 73-122, 2022.
[22]. R. Saxena, V. Sharma, A. R. Saxena, and A. Patel, "Harnessing AI and Gut Microbiome Research for Precision Health," Journal of Artificial Intelligence General Science (JAIGS) ISSN: 3006-4023, vol. 3, no. 1, pp. 74-88, 2024.
[23]. N. V. Matusheski et al., "Diets, nutrients, genes, and the microbiome: recent advances in personalized nutrition," British Journal of Nutrition, vol. 126, no. 10, pp. 1489-1497, 2021.
[24]. B. J. Mortazavi and R. Gutierrez-Osuna, "A review of digital innovations for diet monitoring and precision nutrition," Journal of Diabetes Science and Technology, vol. 17, no. 1, pp. 217-223, 2023.
[25]. B. V. R. e Silva, M. G. Rad, J. Cui, M. McCabe, and K. Pan, "A mobile-based diet monitoring system for obesity management," Journal of Health & Medical Informatics, vol. 9, no. 2, p. 307, 2018.
[26]. T. Khater, H. Tawfik, and B. Singh, "Explainable artificial intelligence for investigating the effect of lifestyle factors on obesity," Intelligent Systems with Applications, vol. 23, p. 200427, 2024.
[27]. S. Lee and J. Chun, "Identification of important features in overweight and obesity among Korean adolescents using machine learning," Children and Youth Services Review, vol. 161, p. 107644, 2024.
[28]. A. Gutiérrez-Gallego et al., "Combination of Machine Learning Techniques to Predict Overweight/Obesity in Adults," Journal of Personalized Medicine, vol. 14, no. 8, p. 816, 2024.
[29]. F. M. Delpino et al., "Does machine learning have a high performance to predict obesity among adults and older adults? A systematic review and meta-analysis, "Nutrition, Metabolism and Cardiovascular Diseases, vol. 34, no. 9, pp. 2034-2045, 2024.
[30]. D. D. Solomon et al., "Hybrid majority voting: Prediction and classification model for obesity," Diagnostics, vol. 13, no. 15, p. 2610, 2023.
[31]. R. C. Cervantes and U. M. Palacio, "Estimation of obesity levels based on computational intelligence," Informatics in Medicine Unlocked, vol. 21, p. 100472, 2020.
[32]. Z. Lin et al., "Machine learning to identify metabolic subtypes of obesity: a multi-center study," Frontiers in Endocrinology, vol. 12, p. 713592, 2021.
[33]. F. Greco and C. A. Mallio, "Artificial intelligence and abdominal adipose tissue analysis: a literature review," Quantitative imaging in medicine and surgery, vol. 11, no. 10, p. 4461, 2021.
[34]. M. K. Mahadi, R. Rahad, A. Noman, S. Ishrat, and F. Faisal, "Understanding Machine Learning & its Application in Obesity Estimation by Explainable AI," in 2024 International Conference on Inventive Computation Technologies (ICICT), 2024: IEEE, pp. 112-117.
[35]. M. Dirik, "Application of machine learning techniques for obesity prediction: a comparative study," Journal of Complexity in Health Sciences, vol. 6, no. 2, pp. 16-34, 2023.
[36]. A. Maulana, R. P. F. Afidh, N. B. Maulydia, G. M. Idroes, and S. Rahimah, "Predicting obesity levels with high accuracy: Insights from a CatBoost machine learning model," Infolitika Journal of Data Science, vol. 2, no. 1, pp. 17-27, 2024.
[37]. B. Wang and M. Torriani, "Artificial intelligence in the evaluation of body composition," in Seminars in Musculoskeletal Radiology, 2020, vol. 24, no. 01: Thieme Medical Publishers, pp. 030-037.
[38]. G. L. Farina, C. Orlandi, H. Lukaski, and L. Nescolarde, "Digital single-image smartphone assessment of total body fat and abdominal fat using machine learning," Sensors, vol. 22, no. 21, p. 8365, 2022.
[39]. N. D. Peterson, K. R. Middleton, L. M. Nackers, K. E. Medina, V. A. Milsom, and M. G. Perri, "Dietary self‐monitoring and long‐term success with Weight Loss," Obesity, vol. 22, no. 9, pp. 1962-1967, 2014.
[40]. T. L. Burrows, Y. Y. Ho, M. E. Rollo, and C. E. Collins, "Validity of dietary assessment methods when compared to the method of doubly labeled water: a systematic review in adults," Frontiers in endocrinology, vol. 10, p. 850, 2019.
[41]. S. Mezgec and B. Koroušić Seljak, "NutriNet: a deep learning food and drink image recognition system for dietary assessment," Nutrients, vol. 9, no. 7, p. 657, 2017.
[42]. S. Mezgec, T. Eftimov, T. Bucher, and B. K. Seljak, "Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment," Public Health Nutrition, vol. 22, no. 7, pp. 1193-1202, 2019.
[43]. S. Mezgec, T. Eftimov, T. Bucher, and B. K. Seljak, "Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment," Public Health Nutrition, vol. 22, no. 7, pp. 1193-1202, 2019.
[44]. C. K. Martin, A. C. Miller, D. M. Thomas, C. M. Champagne, H. Han, and T. Church, "Efficacy of Smart LossSM, a smartphone‐based weight loss intervention: Results from a randomized controlled trial," Obesity, vol. 23, no. 5, pp. 935-942, 2015.
Cite this article
Wang,Z. (2025). Research and Application Prospects Analysis of Artificial Intelligence and Machine Learning in Weight Loss. Theoretical and Natural Science,113,18-25.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. E. J. A. Ataey, D. Adham, and E. Moradi-Asl, "The relationship between obesity, overweight, and the human development index in World Health Organization Eastern Mediterranean Region countries," World Health Organization Obesity and Overweight, 2022.
[2]. "World Health Organization Obesity and Overweight," https://www.who.int/news/item/04-03-2022-world-obesity-day-2022-accelerating-action-to-stop-obesity, 2022.
[3]. A. A. K. Kolahi et al., A. Moghisi, Y. S. Ekhtiari, "Socio-demographic determinants of obesity indexes in Iran: findings from a nationwide steps survey," 2018.
[4]. U. G. G. M. Tremmel, P. M. Nilsson, S. Saha, "Economic burden of obesity: a systematic literature review," International Journal of Environmental Research and Public Health, 2017.
[5]. D. Albuquerque, C. Nóbrega, L. Manco, and C. Padez, "The contribution of genetics and environment to obesity," British medical bulletin, vol. 123, no. 1, pp. 159-173, 2017.
[6]. K. Gawlik, Zwierzchowska, A., & Celebańska, D. (2018). Impact of physical activity on "Impact of physical activity on obesity and lipid profile of adults with intellectual disability," Wiley Online Library, 2018.
[7]. F. Ferdowsy, K. S. A. Rahi, M. I. Jabiullah, and M. T. Habib, "A machine learning approach for obesity risk prediction," Current Research in Behavioral Sciences, vol. 2, p. 100053, 2021.
[8]. M. Safaei, E. A. Sundararajan, M. Driss, W. Boulila, and A. Shapi'i, "A systematic literature review on obesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to predict obesity," Computers in biology and medicine, vol. 136, p. 104754, 2021.
[9]. K. Sweatt, Garvey, W. T., & Martins, C., "Strengths and Limitations of BMI in the Diagnosis of Obesity: What is the Path Forward?" Current Obesity Reports, 2024.
[10]. A. Triantafyllidis et al., "Computerized decision support and machine learning applications for the prevention and treatment of childhood obesity: A systematic review of the literature," Artificial Intelligence in Medicine, vol. 104, p. 101844, 2020.
[11]. A. R. Rahmanti et al., "SlimMe, a chatbot with artificial empathy for personal Weight Loss: system design and finding," Frontiers in Nutrition, vol. 9, p. 870775, 2022.
[12]. T. Miyazawa et al., "Artificial intelligence in food science and nutrition: a narrative review," Nutrition Reviews, vol. 80, no. 12, pp. 2288-2300, 2022.
[13]. A. Bond, K. Mccay, and S. Lal, "Artificial intelligence & clinical nutrition: What the future might have in store," Clinical Nutrition ESPEN, vol. 57, pp. 542-549, 2023.
[14]. T. P. Theodore Armand, K. A. Nfor, J.-I. Kim, and H.-C. Kim, "Applications of artificial intelligence, machine learning, and deep learning in nutrition: a systematic review," Nutrients, vol. 16, no. 7, p. 1073, 2024.
[15]. A. Sosa-Holwerda, O.-H. Park, K. Albracht-Schulte, S. Niraula, L. Thompson, and W. Oldewage-Theron, "The role of artificial intelligence in nutrition research: a scoping review," Nutrients, vol. 16, no. 13, p. 2066, 2024.
[16]. J. Zhu and G. Wang, "Artificial intelligence technology for food nutrition," vol. 15, ed.: MDPI, 2023, p. 4562.
[17]. N. Begum, A. Goyal, and S. Sharma, "Artificial Intelligence-Based Food Calories Estimation Methods in Diet Assessment Research," in Artificial Intelligence Applications in Agriculture and Food Quality Improvement: IGI Global, 2022, pp. 276-290.
[18]. M. Roy, S. Das, and A. T. Protity, "OBESEYE: Interpretable Diet Recommender for Obesity Management using Machine Learning and Explainable AI," arXiv preprint arXiv:2308.02796, 2023.
[19]. N. Varshney, N. Jadhav, K. Gupta, N. R. Mate, A. Rose, and P. Kumar, "Personalized Dietary Recommendations Using Machine Learning: A Comprehensive Review," in 2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), 2023, vol. 1: IEEE, pp. 1-6.
[20]. V. S. Voruganti, "Precision nutrition: recent advances in obesity," Physiology, vol. 38, no. 1, pp. 42-50, 2023.
[21]. D. P. Panagoulias, D. N. Sotiropoulos, and G. A. Tsihrintzis, "Towards personalized nutrition applications with nutritional biomarkers and machine learning," Advances in Assistive Technologies: Selected Papers in Honour of Professor Nikolaos G. Bourbakis – Vol. 3, pp. 73-122, 2022.
[22]. R. Saxena, V. Sharma, A. R. Saxena, and A. Patel, "Harnessing AI and Gut Microbiome Research for Precision Health," Journal of Artificial Intelligence General Science (JAIGS) ISSN: 3006-4023, vol. 3, no. 1, pp. 74-88, 2024.
[23]. N. V. Matusheski et al., "Diets, nutrients, genes, and the microbiome: recent advances in personalized nutrition," British Journal of Nutrition, vol. 126, no. 10, pp. 1489-1497, 2021.
[24]. B. J. Mortazavi and R. Gutierrez-Osuna, "A review of digital innovations for diet monitoring and precision nutrition," Journal of Diabetes Science and Technology, vol. 17, no. 1, pp. 217-223, 2023.
[25]. B. V. R. e Silva, M. G. Rad, J. Cui, M. McCabe, and K. Pan, "A mobile-based diet monitoring system for obesity management," Journal of Health & Medical Informatics, vol. 9, no. 2, p. 307, 2018.
[26]. T. Khater, H. Tawfik, and B. Singh, "Explainable artificial intelligence for investigating the effect of lifestyle factors on obesity," Intelligent Systems with Applications, vol. 23, p. 200427, 2024.
[27]. S. Lee and J. Chun, "Identification of important features in overweight and obesity among Korean adolescents using machine learning," Children and Youth Services Review, vol. 161, p. 107644, 2024.
[28]. A. Gutiérrez-Gallego et al., "Combination of Machine Learning Techniques to Predict Overweight/Obesity in Adults," Journal of Personalized Medicine, vol. 14, no. 8, p. 816, 2024.
[29]. F. M. Delpino et al., "Does machine learning have a high performance to predict obesity among adults and older adults? A systematic review and meta-analysis, "Nutrition, Metabolism and Cardiovascular Diseases, vol. 34, no. 9, pp. 2034-2045, 2024.
[30]. D. D. Solomon et al., "Hybrid majority voting: Prediction and classification model for obesity," Diagnostics, vol. 13, no. 15, p. 2610, 2023.
[31]. R. C. Cervantes and U. M. Palacio, "Estimation of obesity levels based on computational intelligence," Informatics in Medicine Unlocked, vol. 21, p. 100472, 2020.
[32]. Z. Lin et al., "Machine learning to identify metabolic subtypes of obesity: a multi-center study," Frontiers in Endocrinology, vol. 12, p. 713592, 2021.
[33]. F. Greco and C. A. Mallio, "Artificial intelligence and abdominal adipose tissue analysis: a literature review," Quantitative imaging in medicine and surgery, vol. 11, no. 10, p. 4461, 2021.
[34]. M. K. Mahadi, R. Rahad, A. Noman, S. Ishrat, and F. Faisal, "Understanding Machine Learning & its Application in Obesity Estimation by Explainable AI," in 2024 International Conference on Inventive Computation Technologies (ICICT), 2024: IEEE, pp. 112-117.
[35]. M. Dirik, "Application of machine learning techniques for obesity prediction: a comparative study," Journal of Complexity in Health Sciences, vol. 6, no. 2, pp. 16-34, 2023.
[36]. A. Maulana, R. P. F. Afidh, N. B. Maulydia, G. M. Idroes, and S. Rahimah, "Predicting obesity levels with high accuracy: Insights from a CatBoost machine learning model," Infolitika Journal of Data Science, vol. 2, no. 1, pp. 17-27, 2024.
[37]. B. Wang and M. Torriani, "Artificial intelligence in the evaluation of body composition," in Seminars in Musculoskeletal Radiology, 2020, vol. 24, no. 01: Thieme Medical Publishers, pp. 030-037.
[38]. G. L. Farina, C. Orlandi, H. Lukaski, and L. Nescolarde, "Digital single-image smartphone assessment of total body fat and abdominal fat using machine learning," Sensors, vol. 22, no. 21, p. 8365, 2022.
[39]. N. D. Peterson, K. R. Middleton, L. M. Nackers, K. E. Medina, V. A. Milsom, and M. G. Perri, "Dietary self‐monitoring and long‐term success with Weight Loss," Obesity, vol. 22, no. 9, pp. 1962-1967, 2014.
[40]. T. L. Burrows, Y. Y. Ho, M. E. Rollo, and C. E. Collins, "Validity of dietary assessment methods when compared to the method of doubly labeled water: a systematic review in adults," Frontiers in endocrinology, vol. 10, p. 850, 2019.
[41]. S. Mezgec and B. Koroušić Seljak, "NutriNet: a deep learning food and drink image recognition system for dietary assessment," Nutrients, vol. 9, no. 7, p. 657, 2017.
[42]. S. Mezgec, T. Eftimov, T. Bucher, and B. K. Seljak, "Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment," Public Health Nutrition, vol. 22, no. 7, pp. 1193-1202, 2019.
[43]. S. Mezgec, T. Eftimov, T. Bucher, and B. K. Seljak, "Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment," Public Health Nutrition, vol. 22, no. 7, pp. 1193-1202, 2019.
[44]. C. K. Martin, A. C. Miller, D. M. Thomas, C. M. Champagne, H. Han, and T. Church, "Efficacy of Smart LossSM, a smartphone‐based weight loss intervention: Results from a randomized controlled trial," Obesity, vol. 23, no. 5, pp. 935-942, 2015.