Machine learning in risk assessment for microvascular head and neck surgery.

Journal: European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Published Date: Jun 1, 2025

Abstract

PURPOSE: The integration of machine learning (ML) into microvascular surgery for the head and neck offers significant potential to enhance risk stratification, outcome prediction, and decision support. Traditional risk assessment methods are often limited in addressing the dynamic complexity of surgical outcomes. ML can analyze preoperative, intraoperative, and postoperative data to optimize patient management, minimize complications, and improve both functional and aesthetic results.

Authors

  • Gabriele Monarchi
    Department of Medicine, Section of Maxillo-Facial Surgery, University of Siena, Viale Bracci, Siena, 53100, Italy. gabriele.monarchi@gmail.com.
  • Davide Buso
    Fondazione Cà Granda I.R.C.C.S. Ospedale Maggiore Policlinico di Milano, Milan, Italy.
  • Chiara Paolantonio
    Department of Oral and Maxillo Facial Sciences, Policlinico Umberto I "La Sapienza" University of Rome, Rome, Italy.
  • Suhayeb Saidam
    Faculty of Dentistry, Oral and Maxillofacial Surgeon, Al-Ahliyya Amman University, Amman, Jordan.
  • Aldo Bruno Giannì
    Maxillo-Facial and Dental Unit, Fondazione Ca' Granda IRCCS Ospedale Maggiore Policlinico, Milan, Italy.
  • Valentino Valentini
    Department of Oral and Maxillo Facial Sciences, Policlinico Umberto I "La Sapienza" University of Rome, Rome, Italy.
  • Antonio Tullio
    Department of Surgery and Biomedical Sciences, Section of Maxillo-Facial Surgery, University of Perugia, Piazzale Gambuli 1, Perugia, 06129, Italy.

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