AIMC Topic: Weight Reduction Programs

Clear Filters Showing 1 to 6 of 6 articles

Uncovering key factors in weight loss effectiveness through machine learning.

International journal of obesity (2005) May 6, 2025
BACKGROUND/OBJECTIVES: One of the main challenges in weight loss is the dramatic interindividual variability in response to treatment. We aim to systematically identify factors relevant to weight loss effectiveness using machine learning (ML).
Humans Weight Loss Machine Learning Treatment Outcome Adult Body Mass Index Male Female Middle Aged Exercise Cognitive Behavioral Therapy Boosting Machine Learning Algorithms Obesity Weight Reduction Programs Motivation
View on PubMed DOI

Interpretable Conditional Recurrent Neural Network for Weight Change Prediction: Algorithm Development and Validation Study.

JMIR mHealth and uHealth Mar 29, 2021
BACKGROUND: In recent years, mobile-based interventions have received more attention as an alternative to on-site obesity management. Despite increased mobile interventions for obesity, there are lost opportunities to achieve better outcomes due to t...
Humans Neural Networks, Computer Artificial Intelligence United States Cross-Sectional Studies Weight Reduction Programs Weight Loss Male
View on PubMed DOI

Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?

Journal of behavioral medicine Aug 25, 2018
Behavioral weight loss (WL) trials show that, on average, participants regain lost weight unless provided long-term, intensive-and thus costly-intervention. Optimization solutions have shown mixed success. The artificial intelligence principle of "re...
Humans Artificial Intelligence Behavior Therapy Weight Loss Weight Reduction Programs Longitudinal Studies Adult Text Messaging Male Reinforcement, Psychology Middle Aged Female Aged Obesity
View on PubMed DOI

Application of Machine Learning to Predict Dietary Lapses During Weight Loss.

Journal of diabetes science and technology May 24, 2018
BACKGROUND: Individuals who adhere to dietary guidelines provided during weight loss interventions tend to be more successful with weight control. Any deviation from dietary guidelines can be referred to as a "lapse." There is a growing body of resea...
Diet, Reducing Weight Reduction Programs Ecological Momentary Assessment Obesity Patient Compliance Mobile Applications Humans Overweight Machine Learning Adult Male Algorithms Smartphone Female
View on PubMed DOI

Randomized controlled trial of OnTrack, a just-in-time adaptive intervention designed to enhance weight loss.

Translational behavioral medicine Nov 25, 2019
Individual instances of nonadherence to reduced calorie dietary prescriptions, that is, dietary lapses, represent a key challenge for weight management. Just-in-time adaptive interventions (JITAIs), which collect and analyze data in real time to deli...
Patient Compliance Telemedicine Patient Satisfaction Overweight Obesity Outcome and Process Assessment, Health Care Weight Reduction Programs Female Adult Risk Assessment Mobile Applications Male Humans Machine Learning
View on PubMed DOI

INSIGHTS FROM MACHINE-LEARNED DIET SUCCESS PREDICTION.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2016
To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider "quantified self" movement and many opt-in...
Weight Reduction Programs Mobile Applications Algorithms Computational Biology Diet, Reducing Energy Intake Humans Data Mining Diet Records Cluster Analysis Machine Learning Energy Metabolism
View on PubMed
Popular Topics
Recent Journals