Histopathology‐validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo‐progression in glioblastoma - Akbari, Hamed; Rathore, Saima; Bakas, Spyridon; Nasrallah, MacLean P.; Shukla, Gaurav; Mamourian, Elizabeth; Rozycki, Martin; Bagley, Stephen J.; Rudie, Jeffrey D.; Flanders, Adam E.; Dicker, Adam P.; Desai, Arati S.; et al. (Cancer, 2020)
Keywords: Accuracy; Adult; Aged; Aged, 80 and over; Angiogenesis; Biomarkers; Biomarkers, Tumor; Brain cancer; Brain Neoplasms - diagnostic imaging; Brain Neoplasms - pathology; Chemoradiotherapy; Disease Progression; Feature extraction; Female; Glioblastoma; Glioblastoma - diagnostic imaging; Glioblastoma - pathology; Histopathology; Humans; Image acquisition; Learning algorithms; Machine Learning; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medical imaging; Middle Aged; Multivariate analysis; Oncology; Patients; pseudo‐progression; radiographic biomarker; Replication; Toolkits; true progression; pseudo-progression; true progression; glioblastoma; machine learning; radiographic biomarker