Predicting Surgical Outcomes and Optimizing Patients for Surgery Using AI
Year: 2026
Type: article
Abstract: Artificial intelligence (AI) platforms and machine learning (ML) algorithms provide the ability to utilize large amounts of electronically available data and leverage them to augment physicians' risk assessment and predictive abilities. These tools allow for refinement and/or reimagination of current tools aimed at predicting and optimizing outcomes in the perioperative period. In this section, we review AI and ML construction and implementation, the current state of predictive model use in surgical patients during the perioperative period, and discuss opportunities for integration into clinical care to optimize patients for surgery, improve perioperative patient care, and enable earlier detection of postoperative complications. We conclude with a discussion of limitations of AI and ML tools, along with points for consideration regarding their implementation in perioperative surgical care.
DOI: 10.1055/a-2769-1109
Authors: Neal Bhutiani, Abhineet Uppal
Institutions: University of Louisville, Emory University
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7123346495