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Evaluating the performance of artificial intelligence based software for digital mammography characterization
Vasilev Y.A., Kolsanov A.V., Arzamasov K.M., Vladzymyrskyy A.V., Omelyanskaya O.V., Semenov S.S., Axenova L.E.
Radiomics and artificial intelligence for predicting response to neoadjuvant drug therapy in patients with breast cancer: a review
Suleymanova M.M., Karmazanovsky G.G., Kondratyev E.V., Popov A.Y., Nechaev V.A., Ermoshchenkova M.V., Kuzmina E.S.
Classification of the presence of malignant lesions on mammogram using deep learning
Ibragimov A.A., Senotrusova S.A., Litvinov A.A., Beliaeva A.A., Ushakov E.N., Markin Y.V.
Double-reading mammograms using artificial intelligence technologies: A new model of mass preventive examination organization
Vasilev Y.A., Tyrov I.A., Vladzymyrskyy A.V., Arzamasov K.M., Shulkin I.M., Kozhikhina D.D., Pestrenin L.D.
Diseases and abnormalities of the nipple-areolar complex: a case report series
Karanadze E.N., Sinitsyn V.E., Karanadze M.A.
Does aggregating results of AI system for mammography with ML meta-model improve quality of malignancy detection?
Nikitin E.D.
Comparative study of the digital mammography data analysis system based on artificial intelligence “Celsus” and radiologists
Pavlovich P.I., Bronov O.Y., Kapninsky A.A., Abovich Y.A., Rychagova N.I.
The role of mammography in breast cancer radiomics
Govorukhina V.G., Semenov S.S., Gelezhe P.B., Didenko V.V., Morozov S.P., Andreychenko A.E.
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