Utilizing Artificial Intelligence for Predicting Postoperative Complications in Breast Reduction Surgery: A Comprehensive Retrospective Analysis of Predictive Features and Outcomes.

Journal: Aesthetic surgery journal

PMID: 39899336

Abstract

BACKGROUND: Breast reduction is a common procedure with growing rates in the United States of America, aimed at alleviating the physical and psychological burdens of macromastia. Despite high success rates, it carries a risk of complications, with incidence rates ranging from 6.2% to 43%.

Authors

Gon Shoham
Tom Zuckerman
Ehud Fliss
Orel Govrin
Arik Zaretski
Roei Singolda
Daniel J Kedar
David Leshem
Ehab Madah
Ehud Arad
Yoav Barnea

Keywords

Adult Artificial Intelligence Breast Decision Trees Female Humans Hypertrophy Machine Learning Mammaplasty Middle Aged Postoperative Complications Predictive Value of Tests Retrospective Studies Risk Assessment ROC Curve Young Adult

External Resources

View on PubMed Access via DOI PubMed (39899336)

Utilizing Artificial Intelligence for Predicting Postoperative Complications in Breast Reduction Surgery: A Comprehensive Retrospective Analysis of Predictive Features and Outcomes.

Abstract

Authors

Keywords

External Resources

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