期刊
SURGICAL INFECTIONS
卷 22, 期 6, 页码 626-634出版社
MARY ANN LIEBERT, INC
DOI: 10.1089/sur.2021.007
关键词
artificial intelligence; big data; machine learning
This article reviews the growing use of machine learning and artificial intelligence in medical research, particularly in the field of surgical infection research. It provides a conceptual overview and concrete examples of ML/AI techniques, highlighting their potential role in clinical decision support and therapy discovery.
Background: The use of machine learning (ML) and artificial intelligence (AI) in medical research continues to grow as the amount and availability of clinical data expands. These techniques allow complex interpretation of data and capture non-linear relations not immediately apparent by classic statistical techniques. Methods: This review of the ML/AI literature provides a brief overview for practicing surgeons and clinicians of the current and future roles these methods will have within surgical infection research. Results: A conceptual overview of the techniques is provided along with concrete examples in the surgical infections literature. Further examples of ML/AI techniques in clinical decision support as well as therapy discovery with model-based deep reinforcement learning are illustrated. Conclusions: Artificial intelligence and ML are important and increasingly utilized techniques within the expanding body of surgical infection research. This article provides a minimal baseline literacy in ML/AI to be able to view such projects in an appropriately critical fashion.
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