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

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

Benchmarking Outcomes in Plastic Surgery: National Complication Rates for Abdominoplasty and Breast Augmentation 'Outcomes Article]

A Novel Artificial Intelligence Model for Symmetry Evaluation in Breast Cancer Patients

The Project Gutenberg ebook of The Step on the Stair, by Anna Katharine Green—A Project Gutenberg eBook

PDF) Unraveling Factors Influencing Early Seroma Formation in Breast Augmentation Surgery

Validating machine learning approaches for prediction of donor related complication in microsurgical breast reconstruction: a retrospective cohort study

Breast Mass Detection in Mammograms via Blending Adversarial Learning

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

Applications of artificial intelligence in plastic and reconstructive surgery: a comprehensive review of the literature

Validating machine learning approaches for prediction of donor related complication in microsurgical breast reconstruction: a retrospective cohort study

Christoph WALLNER, Consultant, MD, MHBA, PhD, Ruhr-Universität Bochum, Bochum, RUB, Department of Plastic Surgery