Artificial Intelligence for Surgical Safety

2020265 citationsJournal Article

Authors

Pietro Mascagni · Istituti di Ricovero e Cura a Carattere Scientifico

Armine Vardazaryan · Centre National de la Recherche Scientifique

Deepak Alapatt · Directorate-General for Interpretation

Takeshi Urade · Institut de Chirurgie Guidée par l'Image

Taha Emre · Centre National de la Recherche Scientifique

Claudio Fiorillo · Agostino Gemelli University Polyclinic

Patrick Pessaux

Abstract

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.

Topics & Keywords

Surgical Simulation and Training Pancreatic and Hepatic Oncology Research Colorectal Cancer Screening and Detection

UN Sustainable Development Goals

Partnerships for the goals

Publication Details

Published in: Annals of Surgery

Volume 275, Issue 5, pp. 955-961

DOI: 10.1097/sla.0000000000004351

Field-Weighted Citation Impact: 24.71