Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities
Merkaj S, Bahar RC, Zeevi T, Lin M, Ikuta I, Bousabarah K, Petersen G, Staib L, Payabvash S, Mongan JT, Cha S, Aboian MS. Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities. Cancers 2022, 14: 2623. PMID: 35681603, PMCID: PMC9179416, DOI: 10.3390/cancers14112623.Peer-Reviewed Original ResearchMachine learning toolsGrade predictionLearning toolsML applicationsClassifier algorithmML modelsClassification methodMedical imagingData sourcesPractices of radiologistsToolGlioma gradingNext stepWorkflowAlgorithmChallengesTechnological innovationImplementationPredictionModelLast decadeSpecific areasDevelopment of a workflow efficient PACS based automated brain tumor segmentation and radiomic feature extraction for clinical implementation (N2.003)
Aboian M, Bousabarah K, Kazarian E, Zeevi T, Holler W, Merkaj S, Petersen G, Bahar R, Subramanian H, Sunku P, Schrickel E, Mahajan A, Malhotra A, Payabvash S, Tocino I, Lin M, Westerhoff M. Development of a workflow efficient PACS based automated brain tumor segmentation and radiomic feature extraction for clinical implementation (N2.003). Neurology 2022, 98 DOI: 10.1212/wnl.98.18_supplement.3146.Peer-Reviewed Original Research