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.
Quantitative analysis of lesion morphology and texture features for diagnostic prediction in breast MRI
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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.