Predicting Prolonged Length of Hospital Stay and Identifying Risk Factors Following Total Ankle Arthroplasty: A Supervised Machine Learning Methodology

  • Tadiwanashe Chirongoma
  • , Andrew Cabrera
  • , Alexander Bouterse
  • , David Chung
  • , Daniel Patton
  • , Anthony Essilfie

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Pages (from-to)557-561
Number of pages5
JournalJournal of Foot and Ankle Surgery
Volume63
Issue number5
DOIs
StatePublished - Sep 1 2024

ASJC Scopus Subject Areas

  • Surgery
  • Orthopedics and Sports Medicine

Keywords

  • 3
  • Ankle arthroplasty
  • Length of stay
  • Machine learning
  • Retrospective comparative study

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