Fedele interpersonale africano bi rads 4a parti Produttività spiegare
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Risk-predicted dual nomograms consisting of clinical and ultrasound factors for downgrading BI-RADS category 4a breast lesions - A multiple centre study
Mammography report: The abnormal Mammogram - Moose and Doc
Characterization of lesions associated with microcalcifi- cations BI-RADS 4A over a 11-year period of stereotactic breast biopsi
Adenosis classified as BI-RADS 4A. a Ultrasound revealed a solid... | Download Scientific Diagram
Reducing the number of unnecessary biopsies of US-BI-RADS 4a lesions through a deep learning method for residents-in-training: a cross-sectional study | BMJ Open
ACR BI-RADS Assessment Category 4 Subdivisions in Diagnostic Mammography: Utilization and Outcomes in the National Mammography Database | Radiology
The added value of digital breast tomosynthesis in improving diagnostic performance of BI-RADS categorization of mammographically indeterminate breast lesions | Insights into Imaging | Full Text
Value of contrast-enhanced mammography combined with the Kaiser score for clinical decision-making regarding tomosynthesis BI-RADS 4A lesions | SpringerLink
ACR BI-RADS Assessment Category 4 Subdivisions in Diagnostic Mammography: Utilization and Outcomes in the National Mammography Database | Radiology
Role of Clinical and Imaging Risk Factors in Predicting Breast Cancer Diagnosis Among BI-RADS 4 Cases - ScienceDirect
Vista de EVALUACIÓN DE LOS VALORES PREDICTIVOS POSITIVOS EN LAS SUBCATEGORIAS BI-RADS® 4 DE BIOPSIAS PERCUTÁNEAS Y COMPARACIÓN CON VALORES ACR BI-RADS® 5TA EDICIÓN. | Revista de Imagenología
Pathological results and BI-RADS classifications of the breast lesions | Download Scientific Diagram
Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI- RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS | Scientific Reports
The Values of Combined and Sub-Stratified Imaging Scores with Ultrasonography and Mammography in Breast Cancer Subtypes | PLOS ONE
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Frontiers | Diagnostic Value of Breast Lesions Between Deep Learning-Based Computer-Aided Diagnosis System and Experienced Radiologists: Comparison the Performance Between Symptomatic and Asymptomatic Patients