A Machine Learning Approach to Identify Previously Unconsidered Causes for Complications in Aesthetic Breast Augmentation
Validating machine learning approaches for prediction of donor related complication in microsurgical breast reconstruction: a retrospective cohort study
Artificial Intelligence in Plastic Surgery: Applications and Challenges
Deep learning in breast radiology: current progress and future directions
A Machine Learning Method for Nipple-Areola Complex Localization for Chest Masculinization Surgery
Benchmarking Outcomes in Plastic Surgery: National Complication Rates for Abdominoplasty and Breast Augmentation 'Outcomes Article]
Patient Experience Library
Benchmarking Outcomes in Plastic Surgery: National Complication Rates for Abdominoplasty and Breast Augmentation 'Outcomes Article]
A Machine Learning Approach to Identify Previously Unconsidered Causes for Complications in Aesthetic Breast Augmentation
Validating machine learning approaches for prediction of donor related complication in microsurgical breast reconstruction: a retrospective cohort study
An optimized deep learning architecture for breast cancer diagnosis based on improved marine predators algorithm
EUSci #25 - What Science Got Wrong by EUSci Media - Issuu
Christoph WALLNER, Consultant, MD, MHBA, PhD, Ruhr-Universität Bochum, Bochum, RUB, Department of Plastic Surgery
Validating machine learning approaches for prediction of donor related complication in microsurgical breast reconstruction: a retrospective cohort study
A generative adversarial network-based abnormality detection using only normal images for model training with application to digital breast tomosynthesis
