A Machine Learning Approach to Predicting Donor Site Complications Following DIEP Flap Harvest
Conclusion This study demonstrates that body mass index is superior to radiographic features of obesity in predicting donor site complications following DIEP flap harvest. Other predictors include older age and longer surgery duration. Our logistic regression machine learning model has the potential to quantify the risk of donor site complications. [...] Thieme Medical Publishers, Inc. 333 Seventh Avenue, 18th Floor, New York, NY 10001, USAArticle in Thieme eJournals: Table of contents | Abstract | Full text
Source: Journal of Reconstructive Microsurgery - Category: Surgery Authors: Huang, Hao Lu Wang, Marcos Chen, Yunchan Chadab, Tara M. Vernice, Nicholas A. Otterburn, David M. Tags: Original Article Source Type: research
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