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What is Machine Learning for Obesity Risk Prediction about?

This study investigates the application of machine learning (ML) techniques to predict obesity risk using a US health administrative claims database, revealing that obesity is often underreported in claims data. The research found that while the positive predictive value of obesity diagnosis codes is high, their sensitivity is low, indicating many individuals with obesity lack a diagnosis code. The best-performing ML model, XGBoost, demonstrated improved prediction accuracy, highlighting the potential for M

Author

Abbs Alazhari

Language

EN