Predicting Reduction Mammaplasty Total Resection Weight With Machine Learning.

Journal: Annals of plastic surgery
PMID: 38833662

Abstract

BACKGROUND: Machine learning (ML) is a form of artificial intelligence that has been used to create better predictive models in medicine. Using ML algorithms, we sought to create a predictive model for breast resection weight based on anthropometric measurements.

Authors

  • Michelle Y Seu
  • Nikki Rezania
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.
  • Carolyn E Murray
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.
  • Mark T Qiao
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.
  • Sydney Arnold
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.
  • Charalampos Siotos
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.
  • Jennifer Ferraro
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.
  • Hossein E Jazayeri
    Section of Oral and Maxillofacial Surgery, Department of Surgery, Michigan Medicine, Ann Arbor, MI.
  • Keith Hood
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.
  • Deana Shenaq
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.
  • George Kokosis
    From the Division of Plastic & Reconstructive Surgery, Rush University Medical Center, Chicago, IL.

Keywords

External Resources

Popular Topics
Recent Journals