Extensive review on the role of machine learning for multifactorial genetic disorders prediction

DD Solomon, Sonia, K Kumar, K Kanwar, S Iyer… - … Methods in Engineering, 2024 - Springer
The culture of employing machine learning driven assistance and decision making is
currently adopted by a variety of industries. Artificial intelligence encompasses a wide range …

A comprehensive analysis of artificial intelligence techniques for the prediction and prognosis of lifestyle diseases

K Modi, I Singh, Y Kumar - Archives of Computational Methods in …, 2023 - Springer
Artificial intelligence is the fastest growing data-driven technology and is currently used in all
major fields and reduces the work of humans. Artificial intelligence can analyse extensive …

Predicting risk of obesity and meal planning to reduce the obese in adulthood using artificial intelligence

R Kaur, R Kumar, M Gupta - Endocrine, 2022 - Springer
Background An unhealthy diet or excessive amount of food intake creates obesity issues in
human beings that further may cause several diseases such as Polycystic Ovary Syndrome …

Predicting body fat using a novel fuzzy-weighted approach optimized by the whale optimization algorithm

Z Fan, J Gou - Expert Systems with Applications, 2023 - Elsevier
Obesity, termed as excessive body fat, is a major public health problem. Being able to
accurately predict body fat percentage provides an opportunity for making appropriate …

Using machine learning to predict obesity based on genome-wide and epigenome-wide gene–gene and gene–diet interactions

YC Lee, JJ Christensen, LD Parnell, CE Smith… - Frontiers in …, 2022 - frontiersin.org
Obesity is associated with many chronic diseases that impair healthy aging and is governed
by genetic, epigenetic, and environmental factors and their complex interactions. This study …

Modeling and Optimization with Artificial Intelligence in Nutrition

V Knights, M Kolak, G Markovikj, J Gajdoš Kljusurić - Applied Sciences, 2023 - mdpi.com
Featured Application Artificial intelligence offers supreme opportunities for advancement
and application in nutrition. Abstract The use of mathematical modeling and optimization in …

Deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data for enhancing obesity estimation

RZ Zhou, Y Hu, JN Tirabassi, Y Ma, Z Xu - International Journal of Health …, 2022 - Springer
Background Obesity is a serious public health problem. Existing research has shown a
strong association between obesity and an individual's diet and physical activity. If we …

Machine Learning Approaches for Predicting Risk of Cardiometabolic Disease among University Students

D Musleh, A Alkhwaja, I Alkhwaja, M Alghamdi… - Big Data and Cognitive …, 2024 - mdpi.com
Obesity is increasingly becoming a prevalent health concern among adolescents, leading to
significant risks like cardiometabolic diseases (CMDs). The early discovery and diagnosis of …

Age-specific risk factors for the prediction of obesity using a machine learning approach

J Jeon, S Lee, C Oh - Frontiers in Public Health, 2023 - frontiersin.org
Machine Learning is a powerful tool to discover hidden information and relationships in
various data-driven research fields. Obesity is an extremely complex topic, involving …

Predicting nutritional status for women of childbearing age from their economic, health, and demographic features: A supervised machine learning approach

MM Khudri, KK Rhee, MS Hasan, KZ Ahsan - Plos one, 2023 - journals.plos.org
Background Malnutrition imposes enormous costs resulting from lost investments in human
capital and increased healthcare expenditures. There is a dearth of research focusing on the …