Accuracy of distinguishing benign, high-risk lesions and malignancies with inductive machine learning models in BIRADS 4 and BIRADS 5 lesions on breast MR examinations.

Abstract

Authors

• Evangelia Panourgias
  First Department of Radiology ('Aretaieio' Hospital), Medical School, National and Kapodistrian University of Athens, 76 V. Sofias 11523, Athens, Greece. Electronic address: epanourgias@yahoo.com.
• Evangelos Karampotsis
  Management and Decision Engineering Laboratory (MDE-Lab), School of Engineering, University of the Aegean, 41 Kountouriotou Street 82100, Chios, Greece. Electronic address: ekarampotsis@aegean.gr.
• Natalia Douma
  First Department of Radiology ('Aretaieio' Hospital), Medical School, National and Kapodistrian University of Athens, 76 V. Sofias 11523, Athens, Greece.
• Charis Bourgioti
  First Department of Radiology ('Aretaieio' Hospital), Medical School, National and Kapodistrian University of Athens, 76 V. Sofias 11523, Athens, Greece.
• Vassilis Koutoulidis
  First Department of Radiology ('Aretaieio' Hospital), Medical School, National and Kapodistrian University of Athens, 76 V. Sofias 11523, Athens, Greece.
• George Rigas
  Breast Clinic, Agios Savvas, Anticancer Hospital of Athens, 171 Alexandras Avenue 11522, Athens, Greece.
• Lia Moulopoulos
  First Department of Radiology ('Aretaieio' Hospital), Medical School, National and Kapodistrian University of Athens, 76 V. Sofias 11523, Athens, Greece.
• Georgios Dounias
  Management and Decision Engineering Laboratory (MDE-Lab), School of Engineering, University of the Aegean, 41 Kountouriotou Street 82100, Chios, Greece.

Keywords

External Resources