Predicting isocitrate dehydrogenase genotype, histological phenotype, and Ki-67 expression level in diffuse gliomas with an advanced contrast analysis of magnetic resonance imaging sequences

BACKGROUND: The present study aimed to establish a robust predictive model based on a machine learning (ML) algorithm providing preoperative noninvasive diagnosis and to further explore the contribution of each magnetic resonance imaging (MRI) sequence to the classification to help select images for...

Descripción completa

Detalles Bibliográficos
Autores principales: Cui, Yuanyuan, Dang, Yixuan, Zhang, Hao, Peng, Hong, Zhang, Jun, Li, Jinhang, Shen, Peiyi, Mao, Cuiping, Ma, Lin, Zhang, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240019/
https://www.ncbi.nlm.nih.gov/pubmed/37284074
http://dx.doi.org/10.21037/qims-22-887

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240019/
https://www.ncbi.nlm.nih.gov/pubmed/37284074
http://dx.doi.org/10.21037/qims-22-887

Ejemplares similares