Related Experiment Video
Updated: Apr 9, 2026

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions
Published on: April 5, 2024
Predicting Surgical Outcomes and Optimizing Patients for Surgery Using AI
Neal Bhutiani1,2,3, Abhineet Uppal4
1Divisions of Surgical Oncology, Department of Surgery, University of Louisville, Louisville, Kentucky, United States.
None:
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.
