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Stud Health Technol Inform ; 309: 238-239, 2023 Oct 20.
Article in English | MEDLINE | ID: mdl-37869849

ABSTRACT

Nowadays, hospitals are facing the need for an accurate prediction of rehospitalizations. Rehospitalizations, indeed, represent both a high financial burden for the hospital and a proxy measure of care quality. The current work aims to address such a problem with an innovative approach, by building a Process Mining-Deep Learning model for the prediction of 6-months rehospitalization of patients hospitalized in a Cardiology specialty at San Raffaele Hospital, starting from their medical history contained in the Patients Hospital Records, with the double purpose of supporting resource planning and identifying at-risk patients.


Subject(s)
Cardiology , Deep Learning , Humans , Patient Readmission , Retrospective Studies , Hospitals
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