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Weight Reduction Programs

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INSIGHTS FROM MACHINE-LEARNED DIET SUCCESS PREDICTION.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
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...

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

Journal of diabetes science and technology
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...

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

Journal of behavioral medicine
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...

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

Translational behavioral medicine
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...

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

JMIR mHealth and uHealth
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...