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Machine learning-based prediction models for home discharge in patients with COVID-19: Development and evaluation using electronic health records.

Ruben D ZapataShu HuangEarl MorrisChang WangChristopher HarleTanja MagocMamoun MardiniTyler J LoftusFrancois P Modave
Published in: PloS one (2023)
This study's findings are crucial for efficiently allocating healthcare resources during pandemics like COVID-19. By harnessing ML techniques and EHR data, we can create predictive tools to identify patients at greater risk of severe symptoms based on their medical histories. The models developed here serve as a foundation for expanding the toolkit available to healthcare professionals and organizations. Additionally, explainable ML methods, such as Shapley Additive Explanations, aid in uncovering underlying data features that inform healthcare decision-making processes.
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