Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning
Gross M, Haider S, Ze’evi T, Huber S, Arora S, Kucukkaya A, Iseke S, Gebauer B, Fleckenstein F, Dewey M, Jaffe A, Strazzabosco M, Chapiro J, Onofrey J. Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning. European Radiology 2024, 34: 6940-6952. PMID: 38536464, PMCID: PMC11399284, DOI: 10.1007/s00330-024-10624-8.Peer-Reviewed Original ResearchContrast-enhanced magnetic resonance imagingMagnetic resonance imagingClinical staging systemTime of diagnosisHepatocellular carcinomaClinical dataMortality risk predictionOverall survivalStaging systemRadiomic featuresManagement of hepatocellular carcinomaPersonalized follow-up strategiesAssociated with OSMethodsThis retrospective studyHepatocellular carcinoma patientsBaseline magnetic resonance imagingMRI radiomics featuresIndependent validation cohortHarrell's C-indexRisk predictionFollow-up strategiesHigh-risk groupPredictive risk scoreRadiomics feature extractionMedian time