A fused BIRADS-morphometric nomogram using logistic regression on 1747 lesions achieves 83.0% accuracy for biopsy recommendation and 83.8% for malignancy prediction, outperforming three radiologists and two ChatGPT models with external validation.
Using a Large Language Model for Breast Imaging Reporting and Data System Classification and Malignancy Prediction to Enhance Breast Ultrasound Diagnosis: Retrospective Study
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Ultrasound-based detection and malignancy prediction of breast lesions eligible for biopsy: A multi-center clinical-scenario study using nomograms, large language models, and radiologist evaluation
A fused BIRADS-morphometric nomogram using logistic regression on 1747 lesions achieves 83.0% accuracy for biopsy recommendation and 83.8% for malignancy prediction, outperforming three radiologists and two ChatGPT models with external validation.