A Machine Learning Algorithm to Identify Patients
Abstract
Risk categorization of individual infection-prone individuals would enable surgeons to closely monitor high-risk patients and take appropriate action early on. This can lessen the negative effects of infection, such higher medical expenses. In order to determine the likelihood of infection in patients with surgically treated tibial shaft fractures, this study developed a machine learning (ML)-derived risk-stratification tool using the SPRINT .
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