Optimizing malignancy prediction: A comparative analysis of transfer learning techniques on EBUS images.

Journal: Clinics (Sao Paulo, Brazil)
Published Date: Jun 14, 2025

Abstract

BACKGROUND: Improving diagnostic accuracy in EBUS image analysis using machine learning is a current challenge. This study aimed to identify the most effective transfer learning model for predicting lymph node malignancy.

Authors

  • Ali Erdem Ozcelik
    Geomatics Engineering, Recep Tayyip Erdogan University, Rize, Turkey.
  • Neslihan Ozcelik
    Pulmonary Medicine, Recep Tayyip Erdogan University, Rize, Turkey.
  • Emre Bendes
    Department of Computer Engineering, Nevşehir Haci Bektas Veli University, Faculty of Engineering-Architecture, Turkey.
  • Gizem Ozcibik Isik
    Department of Thoracic Surgery, Bolu Izzet Baysal State Hospital, Turkey.
  • Omer Topaloglu
    Department of Thoracic Surgery, Recep Tayyip Erdogan University, Faculty of Medicine, Turkey. Electronic address: omer.topaloglu@erdogan.edu.tr.

Keywords

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