Comprehensive Review on the Role of Gut Microbiome in Predicting Obesity Risk using Advanced Machine Learning Approaches

DOI

10.2991/978-94-6239-756-9_25How to use a DOI?

Keywords

Artificial Intelligence; Gut Microbiota; Machine Learning; Metabolic Disorders; Obesity Prediction

Abstract

Obesity has come up to light as the most vital health concerns of the current century, which is leading towards many diseases. According to the WHO (2022), globally obesity has become three times in the last 50 years, which is 1 out of 8 people is having obesity in adults. It is no longer viewed as a result of calories imbalance but genetic factors, gut microbial ecology, food consumed and environments working together leading to obesity. In the recent years many researches indicate that gut microbiota structure and function have a main role in the regulation of metabolic paths, balancing of the energy, and body inflammation, making them more appropriate in understanding obesity origin and development of the chronic diseases. These insights are further enhanced by the emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) methodologies that enable cultured modelling and prediction of obesity risk. If we look into obesity prediction it has been done by considering and trained on traditional obesity predicting markers BMI, waist circumference, lifestyle and inflammatory biomarkers. Addition of the gut microbial factors and use of advanced machine learning can improve the accuracy of the previous results significantly. This comprehensive review integrates peer-reviewed studies that investigates the robust interconnections among gut microbiota, host genetics, dietary composition, and advanced ML models and interpretable AI.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Kriti Sachdeva
AU  - Hema Karande
AU  - Javed Sayyad
PY  - 2026
DA  - 2026/08/31
TI  - Comprehensive Review on the Role of Gut Microbiome in Predicting Obesity Risk using Advanced Machine Learning Approaches
BT  - Proceedings of the Conference on Bioengineering for Global Health (SYMRESEARCH 2.0 2025)
PB  - Atlantis Press
SP  - 359
EP  - 370
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6239-756-9_25
DO  - 10.2991/978-94-6239-756-9_25
ID  - Sachdeva2026
ER  -