Identifying Predictors Associated with Risk of Death or Admission to Intensive Care Unit in Internal Medicine Patients with Sepsis: A Comparison of Statistical Models and Machine Learning Algorithms

• Main Authors: Antonio Mirijello (Author), Andrea Fontana (Author), Antonio Pio Greco (Author), Alberto Tosoni (Author), Angelo D'Agruma (Author), Maria Labonia (Author), Massimiliano Copetti (Author), Pamela Piscitelli (Author), Salvatore De Cosmo (Author), on behalf of the Internal Medicine Sepsis Study Group (Author)
• Format: Book
• Published: MDPI AG, 2023-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

<i>Background:</i> Sepsis is a time-dependent disease: the early recognition of patients at risk for poor outcome is mandatory. <i>Aim:</i> To identify prognostic predictors of the risk of death or admission to intensive care units in a consecutive sample of septic patients,...