Machine Learning Models for Predicting Facial Nerve Palsy in Parotid Gland Surgery for Benign Tumors.

Journal: The Journal of surgical research
Published Date:

Abstract

BACKGROUND: Despite the increasing use of intraoperative facial nerve monitoring during parotid gland surgery (PGS) and the improvement in the preoperative radiological assessment, facial nerve injury (FNI) remains the most severe complication after PGS. Until now, no studies have been published regarding the application of machine learning (ML) for predicting FNI after PGS. We hypothesize that ML would improve the prediction of patients at risk.

Authors

  • Carlos Miguel Chiesa-Estomba
    Osakidetza, Donostia University Hospital, Department of Otorhinolaryngology, San Sebastian, Spain; Biodonostia Health Research Institute, San Sebastian, Spain. Electronic address: chiesaestomba86@gmail.com.
  • Oier Echaniz
    Computational Intelligence Group, Facultad de Informatica UPV/EHU, San Sebastian, Spain.
  • Jon Alexander Sistiaga Suarez
    Osakidetza, Donostia University Hospital, Department of Otorhinolaryngology, San Sebastian, Spain.
  • Jose Angel González-García
    Osakidetza, Donostia University Hospital, Department of Otorhinolaryngology, San Sebastian, Spain.
  • Ekhiñe Larruscain
    Osakidetza, Donostia University Hospital, Department of Otorhinolaryngology, San Sebastian, Spain.
  • Xabier Altuna
    Osakidetza, Donostia University Hospital, Department of Otorhinolaryngology, San Sebastian, Spain; Biodonostia Health Research Institute, San Sebastian, Spain.
  • Alfonso Medela
    LEGIT Health, Bilbao, Spain.
  • Manuel Graña
    Computational Intelligence Group, Faculty of Informatics, Basque Country University (UPV/EHU), Paseo Manuel de Lardizabal 1, 20018 San Sebastian, Spain; Department of Computer Science and Artificial Intelligence, Faculty of Informatics, Basque Country University (UPV/EHU), Paseo Manuel de Lardizabal 1, 20018 San Sebastian, Spain; ENGINE Centre, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland.