Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine

• Published in: Cancers Vol. 13; no. 23; p. 5921
• Main Authors: Fathi Kazerooni, Anahita, Bagley, Stephen J., Akbari, Hamed, Saxena, Sanjay, Bagheri, Sina, Guo, Jun, Chawla, Sanjeev, Nabavizadeh, Ali, Mohan, Suyash, Bakas, Spyridon, Davatzikos, Christos, Nasrallah, MacLean P.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 25.11.2021; MDPI
• Subjects: Biology; Biomarkers; Brain cancer; Brain tumors; Clinical decision making; Clinical outcomes; Clinical trials; Genomics; Glioma; Learning algorithms; Machine learning; Magnetic resonance imaging; Medical imaging; Medical prognosis; Metastases; Oncology; Pathophysiology; Patients; Precision medicine; Predictions; Radiomics; Surgery; Tumors

Machine learning (ML) integrated with medical imaging has introduced new perspectives in precision diagnostics of high-grade gliomas, through radiomics and radiogenomics. This has raised hopes for characterizing noninvasive and in vivo biomarkers for prediction of patient survival, tumor recurrence,...