A Surgeon's Guide to Artificial Intelligence-Driven Predictive Models. Issue 1 (January 2023)

• Record Type: Journal Article
• Authors: Hassan, Abbas M.; Rajesh, Aashish; Asaad, Malke; Nelson, Jonas A.; Coert, J. Henk; Mehrara, Babak J.; Butler, Charles E.
• Is Part Of: American surgeon. Volume 89:Issue 1(2023)
• Page Start: 11
• Page End: 19
• Publication Date: 2023-01
• Subjects: artificial intelligence -- machine learning -- deep learning -- surgery -- predictive model -- surgery -- prediction -- risk assessment; Surgery -- Periodicals; Surgery -- United States -- Periodicals; 617.0973
• DOI: 10.1177/00031348221103648
• Languages: English
• ISSNs: 0003-1348

Abstract

Artificial intelligence (AI) focuses on processing and interpreting complex information as well as identifying relationships and patterns among complex data. Artificial intelligence- and machine learning (ML)-driven predictions have shown promising potential in influencing real-time decisions and improving surgical outcomes by facilitating screening, diagnosis, risk assessment, preoperative planning, and shared decision-making. Fundamental understanding of the algorithms, as well as their development and interpretation, is essential for the evolution of AI in surgery. In this article, we provide surgeons with a fundamental understanding of AI-driven predictive models through an overview of common ML and deep learning algorithms, model development, performance metrics and interpretation. This would serve as a basis for understanding ML-based research, while fostering new ideas and innovations for furthering the reach of this emerging discipline.