November 16, 2020

Artificial Intelligence for Surgical Safety

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Resumen

Deep learning algorithms can be trained to reliably segment hepatocystic anatomy and assess CVS criteria in still laparoscopic images. Surgical-technical partnerships should be encouraged to develop and evaluate deep learning models to improve surgical safety.

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Cite This Study

Mascagni et al. (Mon,) studied this question.

synapsesocial.com/papers/69d6b955f174babf6cab34d2 https://doi.org/https://doi.org/10.1097/sla.0000000000004351

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Formalizing video documentation of the Critical View of Safety in laparoscopic cholecystectomy: a step towards artificial intelligence assistance to improve surgical safety2019 · 61 citations
2A survey on deep learning in medical image analysis2017 · 14,352 citations
3The nature, patterns, clinical outcomes, and financial impact of intraoperative adverse events in emergency surgery2015 · 18 citations
4Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques2019 · 121 citations
5Patient Safety in the Cardiac Operating Room: Human Factors and Teamwork2013 · 325 citations

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