Endometrial Cancer Individualised Scoring System (ECISS): A machine learning-based prediction model of endometrial cancer prognosis.

Shazly, Sherif; Coronado, Pluvio; Yılmaz, Ercan; Melekoglu, RAUF; Sahin, Hanifi; Giannella, Luca; Ciavattini, Andrea; Carpini, Giovanni; Di Giuseppe, Jacopo; Yordanov, Angel; Karakadieva, Konstantina; Nedelcheva, Nevena; Vasileva-Slaveva, Mariela; Alcazar, Juan; Chacon, Enrique; Manzour, Nabil; Vara, Julio; Karaman, Erbil; Karaaslan, Onur; Hacıoğlu, Latif; Korkmaz, Duygu; Onal, Cem; Knez, Jure; Ferrari, Federico; Hosni, Esraa; Mahmoud, Mohamed; Elassall, Gena; Abdo, Mohamed; Mohamed, Yasmin; Abdelbadie, Amr

doi:10.1002/ijgo.14639

Endometrial Cancer Individualised Scoring System (ECISS): A machine learning-based prediction model of endometrial cancer prognosis.

Shazly S. A., Coronado P. J., Yılmaz E., Melekoglu R., Sahin H., Giannella L., ...Daha Fazla

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics, 2022 (SCI-Expanded, Scopus)

Yayın Türü: Makale / Tam Makale
Basım Tarihi: 2022
Doi Numarası: 10.1002/ijgo.14639
Dergi Adı: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, CINAHL, EMBASE, Gender Studies Database, MEDLINE, Public Affairs Index
Anahtar Kelimeler: Artificial intelligence, Disease-free survival, Overall survival, Uterine cancer
İnönü Üniversitesi Adresli: Evet