Health AI Central
Peer-Reviewed Publication
Diagnostics (Basel)2026;16(18)September 15, 2026Journal Article

LUCID: Intelligent Informative Frame Selection in Otoscopy for Enhanced Diagnostic Utility.

Hao Lu1, Muhammet F Demir1, Gabriella I Puchall1, Zian Shang1, Tucker Corwen1, Shalaka Chavan1, Carl D Langefeld2, Amy Zinnia2, Delal Seker3, Muhammad Khalid Khan Niazi4, Aaron C Moberly5, Metin N Gurcan1
1Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
2Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
3Department of Electrical and Electronics Engineering, Dicle University, Diyarbakir 21280, Turkey.
4Department of Pathology, The Ohio State University, Columbus, OH 43210, USA.
5Department of Otolaryngology-Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
PubMed PMC DOI PDF

Abstract

Background/Objectives: Accurate diagnosis of middle ear disease remains challenging because otoscopic interpretation is subjective, while many artificial intelligence models depend on manually selected still frames from video examinations. We aimed to develop and internally evaluate LUCID, a systematic framework for automatically identifying the most informative frames in otoscopy videos. Methods:…

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