Breast Lesion Classification with Multiparametric Breast MRI Using Radiomics and Machine Learning: A Comparison with Radiologists' Performance.

This was further emphasized when we analyzed the subgroup of masses, in which the multiparametric radiomics model with individual BI-RADS descriptors and ADC values provided borderline significance when compared with the accuracy of radiologists based on multiparametric MRI using ADC values (91.7% vs. 86.9%; p = 0.063).

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Based on DCE, only the “radiomics DCE data with BI-RADS model” provided a borderline significant improvement in diagnostic accuracy when compared with radiologists’ assessment of breast lesions using BI-RADS classification.

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