Application of Machine Learning in Predicting Perioperative Outcomes in Patients with Cancer: A Narrative Review for Clinicians
Garry Brydges, Abhineet Uppal, Vijaya Gottumukkala
Abstract
This narrative review explores the utilization of machine learning (ML) and artificial intelligence (AI) models to enhance perioperative cancer care. ML and AI models offer significant potential to improve perioperative cancer care by predicting outcomes and supporting clinical decision-making. Tailored for perioperative professionals including anesthesiologists, surgeons, critical care physicians, nurse anesthetists, and perioperative nurses, this review provides a comprehensive framework for the integration of ML and AI models to enhance patient care delivery throughout the perioperative continuum.
Topics & Concepts
PerioperativeMedicineNarrative reviewPatient careNarrativePerioperative nursingIntensive care medicineMEDLINEMedical physicsMedical educationArtificial intelligenceNursingSurgeryComputer scienceLinguisticsPolitical sciencePhilosophyLawCardiac, Anesthesia and Surgical OutcomesArtificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging