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Application of machine learning models on predicting the length of hospital stay in fragility fracture patients.

Chun-Hei LaiPrudence Kwan-Lam MokWai Wang ChauSheung-Wai Law
Published in: BMC medical informatics and decision making (2024)
Applying ML techniques to improve the quality and efficiency in the healthcare sector is becoming popular in Hong Kong and around the globe, but there has not yet been research related to fragility fracture. The integration of machine learning may be useful for health-care professionals to better identify fragility fracture patients at risk of prolonged hospital stays. These findings underline the usefulness of machine learning techniques in optimizing resource allocation by identifying high risk individuals and providing appropriate management to improve treatment outcome.
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