Novel Machine Learning Approach to Predict and Personalize Length of Stay for Patients Admitted with Syncope from the Emergency Department

We developed a machine learning model to predict the Length of Stay (LoS) for syncope patients in the Emer-gency Department. Addressed the lack of models predicting admission and LoS for syncope cases. Aimed to provide an effective, exploratory tool for personalized prediction of LoS.

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