OBJECTIVES: Diagnosis of cochlear malformation on temporal bone CT images is often difficult because the imaging findings are frequently subtle. Our aim was to assess the utility of deep learning analysis in diagnosing cochlear malformation on temporal bone CT images.
No immediate practice change; the model is a research prototype and requires prospective clinical validation before it could replace or assist expert radiological review of cochlear malformations.
Accurate pre-surgical identification of cochlear malformations is essential for cochlear implant candidacy decisions and surgical planning, and AI-assisted CT reading could reduce missed diagnoses.
- 01A deep learning model was trained to classify cochlear malformations on temporal bone CT images.
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