
Researchers developed a deep learning system using eye-tracking data to enhance AI-powered biopsy image interpretation.
Key Details
- 1The Pathology Expertise Acquisition Network (PEAN) was trained using expert pathologists’ eye movements while reviewing 5,881 skin lesion slides.
- 2PEAN-C achieved 96.3% accuracy and 0.992 AUC on internal data and 93.0% accuracy and 0.984 AUC on external test data, exceeding the next best AI model by 5.5%.
- 3Using pathologist gaze data, the model identifies relevant tissue regions with much less manual labeling burden than traditional pixel-wise annotation.
- 4Integrating PEAN-generated data with other models improved classification accuracy and AUC, statistically significant by paired t-test (p = 0.0053 and 0.0161).
- 5The aim is to scale to personalized diagnosis and multimodal predictive models, leveraging low-cost data collection from expertise monitoring.
Why It Matters

Source
EurekAlert
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