A Machine Learning Approach to Identify Previously Unconsidered Causes for Complications in Aesthetic Breast Augmentation.

Journal: Aesthetic plastic surgery

Published Date: Jul 8, 2022

Abstract

INTRODUCTION: Primary breast augmentation is one of the most commonly requested aesthetic procedures. Considering the large number of procedures performed in connection with a high demand, it is crucial to prevent complications. For this reason, finding and avoiding possible sources of complications is decisive.

Authors

Paolo Montemurro

Akademikliniken, Storängsvägen 10, 11541, Stockholm, Sweden. paolo.montemurro@ak.se.
Marcus Lehnhardt

Department of Plastic Surgery, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bürkle-de-la-Camp Platz 1, 44789, Bochum, Germany.
Björn Behr

Department of Plastic Surgery, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bürkle-de-la-Camp Platz 1, 44789, Bochum, Germany.
Christoph Wallner

Akademikliniken, Storängsvägen 10, 11541, Stockholm, Sweden.

Keywords

Artificial Intelligence Female Humans Machine Learning Mammaplasty Reproducibility of Results

External Resources

View on PubMed Access via DOI PubMed (35802149)

A Machine Learning Approach to Identify Previously Unconsidered Causes for Complications in Aesthetic Breast Augmentation.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals