作者
Carly R Garrow, Karl-Friedrich Kowalewski, Linhong Li, Martin Wagner, Mona W Schmidt, Sandy Engelhardt, Daniel A Hashimoto, Hannes G Kenngott, Sebastian Bodenstedt, Stefanie Speidel, Beat P Müller-Stich, Felix Nickel
发表日期
2021/4/1
来源
Annals of surgery
卷号
273
期号
4
页码范围
684-693
出版商
LWW
简介
Objective:
To provide an overview of ML models and data streams utilized for automated surgical phase recognition.
Background:
Phase recognition identifies different steps and phases of an operation. ML is an evolving technology that allows analysis and interpretation of huge data sets. Automation of phase recognition based on data inputs is essential for optimization of workflow, surgical training, intraoperative assistance, patient safety, and efficiency.
Methods:
A systematic review was performed according to the Cochrane recommendations and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. PubMed, Web of Science, IEEExplore, GoogleScholar, and CiteSeerX were searched. Literature describing phase recognition based on ML models and the capture of intraoperative signals during general surgery procedures was included.
Results:
A total of 2254 titles/abstracts were …
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CR Garrow, KF Kowalewski, L Li, M Wagner… - Annals of surgery, 2021