Artificial Intelligence-Assisted Surgical Quality Assessment: Hype or Hope?

In this issue of the Journal, Zhu and colleagues1 present the external validation of a machine-learning (ML)-based automated surveillance algorithm to detect surgical site infection (SSI) from the electronic healthcare record (EHR). I commend the authors for undertaking an ambitious, technically challenging endeavor and bringing a rigorous method to validate their approach. Overall, the authors conclude that SSI detection algorithms developed in one institution can generalize and be readily applicable to a second institution, therefore giving a practical approach to accelerated chart reviews for surgical site infection detection.
Source: Journal of the American College of Surgeons - Category: Surgery Authors: Tags: Invited Commentary Source Type: research