Key result
This review highlights ten influential papers from the past five years to illustrate the evolution and integration of artificial intelligence in clinical anesthesiology.
Why the study?
The review aimed to explore the ten most cited papers on artificial intelligence in anesthesiology and understand how and when it should be integrated into clinical practice.
This review highlights the transition of AI in anesthesiology from 'black-box' methodologies to more comprehensible 'glass-box' clinical applications.
Answers are grounded in this paper and cite their sources.
May support exploratory AI use in anesthesiology; leaves open need for prospective validation before practice change.
Artificial intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the present review we chose ten influential papers from the last five years and through Kintsugi, shed the light on recent evolution of artificial intelligence in anesthesiology. A comprehensive search in in Medline, Embase, Web of Science and Scopus databases was conducted. Each author searched the databases independently and created a list of six articles that influenced their clinical practice during this period, with a focus on their area of competence. During a subsequent step, each researcher presented his own list and most cited papers were selected to create the final collection of ten articles. In recent years purely methodological works with a cryptic technology (black-box) represented by the intact and static vessel, translated to a "modern artificial intelligence" in clinical practice and comprehensibility (glass-box). The purposes of this review are to explore the ten most cited papers about artificial intelligence in anesthesiology and to understand how and when it should be integrated in clinical practice.
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Bellini et al. (2023) conducted a review in Artificial intelligence in anesthesiology. Artificial intelligence was evaluated. This review highlights ten influential papers from the past five years to illustrate the evolution and integration of artificial intelligence in clinical anesthesiology.
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