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Published on: March 13, 2021
Machine Learning-Based Identification of Obesity from Positive and Unlabelled Electronic Health Records
Vicent Blanes-Selva1, Salvador Tortajada2, Ruth Vilar3
1Instituto Universitario de Tecnologías de la Información y Comunicaciones. Universitat Politècnica de València. Camino de Vera s/n. 46022 Valencia, España.
Introduction:
Prevalence of overweight and obesity are increas- ing in the last decades, and with them, diseases and health conditions such as diabetes, hypertension or cardiovascular diseases. However, hos- pital databases usually do not record such conditions in adults, neither anthropomorfic measures that facilitate their identification.
Methods:
We implemented a machine learning method based on PU (Positive and Unlabelled) Learning to identify obese patients without a diagnose code of obesity in the health records.
Results:
The algorithm presented a high sensitivity (98%) and predicted that around 18% of the patients without a diagnosis were obese. This result is consistent with the report of the WHO.
