Situating Artificial Intelligence in Surgery: A Focus on Disease Severity

Objectives: Artificial intelligence (AI) has numerous applications in surgical quality assurance. We assessed AI accuracy in evaluating the critical view of safety (CVS) and intraoperative events during laparoscopic cholecystectomy. We hypothesized that AI accuracy and intraoperative events are associated with disease severity. Methods: One thousand fifty-one laparoscopic cholecystectomy videos were annotated by AI for disease severity (Parkland Scale), CVS achievement (Strasberg Criteria), and intraoperative events. Surgeons performed focused video review on procedures with ≥1 intraoperative events (n = 335). AI versus surgeon annotation of CVS components and intraoperative events were compared. For all cases (n = 1051), intraoperative-event association with CVS achievement and severity was examined using ordinal logistic regression. Results: Using AI annotation, surgeons reviewed 50 videos/hr. CVS was achieved in ≤10% of cases. Hepatocystic triangle and cystic plate visualization was achieved more often in low-severity cases (P
Source: Annals of Surgery - Category: Surgery Tags: PAPERS CHOSEN FOR PRESENTATION AT THE 2020 ANNUAL MEETING OF THE AMERICAN SURGICAL ASSOCIATION Source Type: research