NI-13 The effectiveness and limitation of survival prediction in primary glioblastoma using machine learning-based texture analysis

Introduction: Clinical application of survival prediction of primary glioblastoma (pGBM) using preoperative images remains challenging due to a lack of robustness and standardization of the method. This research focused on validating a machine learning-based texture analysis model for this purpose u...

Descripción completa

Detalles Bibliográficos
Autores principales: Umehara, Toru, Kinoshita, Manabu, Sasaki, Takahiro, Arita, Hideyuki, Yoshioka, Ema, Shofuda, Tomoko, Kodama, Yoshinori, Hirayama, Ryuichi, Kijima, Noriyuki, Kagawa, Naoki, Okita, Yoshiko, Takano, Koji, Uda, Takehiro, Fukai, Junya, Sakamoto, Daisuke, Mori, Kanji, Kanemura, Yonehiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Supplement Abstracts
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7699060/
http://dx.doi.org/10.1093/noajnl/vdaa143.060

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7699060/
http://dx.doi.org/10.1093/noajnl/vdaa143.060

Ejemplares similares