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Machine Learning and Artificial Intelligence in Surgical Research.

Shruthi Srinivas¹, Andrew J Young²

¹Department of Surgery, The Ohio State University, 370 West 9th Avenue, Columbus, OH 43210, USA.

The Surgical Clinics of North America

|March 22, 2023

Summary

This summary is machine-generated.

Machine learning (ML), a type of artificial intelligence, is revolutionizing surgical research with predictive modeling. ML applications in surgery enhance diagnostics, prognosis, and education for personalized patient care.

Keywords:

Artificial intelligence Machine learning Surgical research

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Area of Science:

Artificial Intelligence in Medicine
Surgical Predictive Modeling
Computational Surgery

Background:

Machine learning (ML), a subset of artificial intelligence (AI), is gaining traction in medical and surgical research.
Historically, ML has been explored for its potential to advance various medical fields.
Its application in surgery is an emerging area focused on predictive capabilities.

Purpose of the Study:

To highlight the role of machine learning in surgical research.
To explore the potential of ML in improving surgical outcomes and patient care.
To identify key research avenues within surgical ML.

Main Methods:

Review of current machine learning applications in surgical research.
Analysis of traditional research metrics in the context of ML.
Identification of ML's role in diagnostics, prognosis, operative timing, and surgical education.

Main Results:

Machine learning is a key component of predictive modeling in surgical research.
ML facilitates advancements across diverse surgical subspecialties.
The integration of ML enhances the personalization and comprehensiveness of medical care.

Conclusions:

Machine learning offers a transformative future for surgical research.
ML enables more precise and individualized patient management strategies.
The continued development of ML in surgery promises significant improvements in healthcare delivery.