| Autor: |
BLANES-SELVA, Vicent, TORTAJADA, Salvador, VILAR, Ruth, VALDIVIESO, Bernardo, GARCÍA-GÓMEZ, Juan M. |
| Zdroj: |
Studies in Health Technology & Informatics; 2020, Vol. 270, p864-868, 5p, 2 Charts |
| Abstrakt: |
Introduction: Prevalence of overweight and obesity are increasing in the last decades, and with them, diseases and health conditions such as diabetes, hypertension or cardiovascular diseases. However, hospital 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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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