Artificial Intelligence for the Identification of Endometrial Malignancies: Application of the Learning Vector Quantizer
Abraham Pouliakis (2nd Department of Pathology, National and Kapodistrian University of Athens, Athens, Greece); Niki Margari (Department of Cytopathology, National and Kapodistrian University of Athens, Athens, Greece); Effrosyni Karakitsou (Department of Biology, University of Barcelona, Barcelona, Spain); Evangelia Alamanou (Department of Obstetrics and Gynecology, Tzaneio Hospital, Athens, Greece); Nikolaos Koureas (2nd Department of Gynecology, St. Savas Hospital, Athens, Greece); George Chrelias (3rd Department of Obstetrics and Gynecology, National and Kapodistrian University of Athens, Athens, Greece); Vasileios Sioulas (3rd Department of Obstetrics and Gynecology, National and Kapodistrian University of Athens, Athens, Greece); Asimakis Pappas (MHTERA Maternity Hospital,Obstetrics and Gynecology, Athens, Greece); Charalambos Chrelias (3rd Department of Obstetrics and Gynecology, National and Kapodistrian University of Athens, Athens, Greece); Emmanouil G. Terzakis (Department of Gynecology, St. Savas Hospital, Athens, Greece); Vasileia Damaskou (2nd Department of Pathology, National and Kapodistrian University of Athens, Athens, Greece); Ioannis G. Panayiotides (2nd Department of Pathology, National and Kapodistrian University of Athens, Athens, Greece); Petros Karakitsos (Department of Cytopathology, National and Kapodistrian University of Athens, Athens, Greece)
ISSN: 2160-9551|EISSN: 2160-956X
https://www.igi-global.com/article/artificial-intelligence-for-the-identification-of-endometrial-malignancies/197804