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Patient Dropouts

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Identification of Psychological Treatment Dropout Predictors Using Machine Learning Models on Italian Patients Living with Overweight and Obesity Ineligible for Bariatric Surgery.

Nutrients
According to the main international guidelines, patients with obesity and psychiatric/psychological disorders who cannot be addressed to surgery are recommended to follow a nutritional approach and a psychological treatment. A total of 94 patients (T...

Machine learning algorithms for prediction of measles one vaccination dropout among 12-23 months children in Ethiopia.

BMJ open
INTRODUCTION: Despite the availability of a safe and effective measles vaccine in Ethiopia, the country has experienced recurrent and significant measles outbreaks, with a nearly fivefold increase in confirmed cases from 2021 to 2023. The WHO has ide...

Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: A Machine Learning Study.

JMIR mental health
BACKGROUND: Digital mental health is a promising paradigm for individualized, patient-driven health care. For example, cognitive bias modification programs that target interpretation biases (cognitive bias modification for interpretation [CBM-I]) can...

Predictors of treatment attrition among individuals in substance use disorder treatment: A machine learning approach.

Addictive behaviors
BACKGROUND: Early treatment discontinuation in substance use disorder treatment settings is common and often difficult to predict. We leveraged a machine learning approach (i.e., random forest) to identify individuals at risk for treatment attrition,...