Radiomics and machine learning for predicting the consistency of benign tumors of the central nervous system: A systematic review
C Koechli, DR Zwahlen, P Schucht… - European journal of …, 2023 - Elsevier
Purpose Predicting the consistency of benign central nervous system (CNS) tumors prior to
surgery helps to improve surgical outcomes. This review summarizes and analyzes the …
surgery helps to improve surgical outcomes. This review summarizes and analyzes the …
Machine learning‑based radiomics models accurately predict Crohn's disease‑related anorectal cancer
Y Horio, J Ikeda, K Matsumoto, S Okada… - Oncology …, 2024 - spandidos-publications.com
The radiological diagnosis of Crohn's disease (CD)-related anorectal cancer is difficult; it is
often found in advanced stages and has a poor prognosis because of the difficulty of …
often found in advanced stages and has a poor prognosis because of the difficulty of …
Differentiation of Pilocytic Astrocytoma from Glioblastoma using a Machine-Learning framework based upon quantitative T1 perfusion MRI
N Vats, A Sengupta, RK Gupta, R Patir… - Magnetic Resonance …, 2023 - Elsevier
Background and purpose Differentiation of pilocytic astrocytoma (PA) from glioblastoma is
difficult using conventional MRI parameters. The purpose of this study was to differentiate …
difficult using conventional MRI parameters. The purpose of this study was to differentiate …