Image-Based Diagnostic Performance of LLMs vs CNNs for Oral Lichen Planus: Example-Guided and Differential Diagnosis.

Journal: International dental journal
Published Date:

Abstract

INTRODUCTION AND AIMS: The overlapping characteristics of oral lichen planus (OLP), a chronic oral mucosal inflammatory condition, with those of other oral lesions, present diagnostic challenges. Large language models (LLMs) with integrated computer-vision capabilities and convolutional neural networks (CNNs) constitute an alternative diagnostic modality. We evaluated the ability of seven LLMs, including both proprietary and open-source models, to detect OLP from intraoral images and generate differential diagnoses.

Authors

  • Paak Rewthamrongsris
    Center of Excellence for Dental Stem Cell Biology, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
  • Jirayu Burapacheep
    Department of Computer Science, Stanford University, Stanford, USA.
  • Ekarat Phattarataratip
    Department of Oral Pathology, Faculty of Dentistry, Chulalongkorn University, Bangkok, 10330, Thailand. ekarat.p@chula.ac.th.
  • Promphakkon Kulthanaamondhita
    Bangkok Hospital Dental Center Holistic Care and Dental Implant, Bangkok Hospital, Bangkok, 10310, Thailand.
  • Antonín Tichý
    Institute of Dental Medicine, First Faculty of Medicine of the Charles University and General University Hospital, Prague, Czech Republic.
  • Falk Schwendicke
    Department of Operative and Preventive Dentistry, Charité - Universitätsmedizin Berlin, Berlin, Germany. falk.schwendicke@charite.de.
  • Thanaphum Osathanon
    Center of Excellence for Dental Stem Cell Biology, Department of Anatomy, Faculty of Dentistry, Chulalongkorn University, Bangkok, 10330, Thailand.
  • Kraisorn Sappayatosok
    Bangkok Hospital Dental Center Holistic Care and Dental Implant, Bangkok Hospital, Bangkok, 10310, Thailand. kraisorn.s@rsu.ac.th.