AI Medical Compendium Topic

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Binge-Eating Disorder

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Interactions between different eating patterns on recurrent binge-eating behavior: A machine learning approach.

The International journal of eating disorders
OBJECTIVE: Previous research has shown that certain eating patterns (rigid restraint, flexible restraint, intuitive eating) are differentially related to binge eating. However, despite the distinctiveness of these eating patterns, evidence suggests t...

Detecting defense mechanisms from Adult Attachment Interview (AAI) transcripts using machine learning.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: Defensive functioning (i.e., unconscious process used to manage real or perceived threats) may play a role in the development of various psychopathologies. It is typically assessed via observer rating measures, however, human coding of def...

Physiological model-based machine learning for classifying patients with binge-eating disorder (BED) from the Oral Glucose Tolerance Test (OGTT) curve.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Binge eating disorder (BED) is the most frequent eating disorder, often confused with obesity, with which it shares several characteristics. Early identification could enable targeted therapeutic interventions. In this study...

Application of Machine Learning Techniques to the Prediction of Onset and Persistence of Binge Eating: A Prospective Study.

European eating disorders review : the journal of the Eating Disorders Association
OBJECTIVE: Machine learning (ML) techniques have shown promise for enhancing prediction of clinical outcomes; however, its application to predicting binge eating has been scarcely explored. We applied ML techniques to predict binge eating onset (vs. ...

Leveraging OGTT derived metabolic features to detect Binge-eating disorder in individuals with high weight: a "seek out" machine learning approach.

Translational psychiatry
Binge eating disorder (BED) carries a 6 times higher risk for obesity and accounts for roughly 30% of type 2 diabetes cases. Timely identification of early glycemic disturbances and comprehensive treatment can impact on the likelihood of associated m...

Determining the Importance of Lifestyle Risk Factors in Predicting Binge Eating Disorder After Bariatric Surgery Using Machine Learning Models and Lifestyle Scores.

Obesity surgery
BACKGROUND: This study was conducted to assess the association between lifestyle risk factors (LRF) and odds of binge eating disorder (BED) 2 years post laparoscopic sleeve gastrectomy (LSG) using lifestyle score (LS) and machine learning (ML) models...