Artificial intelligence in liver cancer — new tools for research and patient management
Calderaro J, Žigutytė L, Truhn D, Jaffe A, Kather J. Artificial intelligence in liver cancer — new tools for research and patient management. Nature Reviews Gastroenterology & Hepatology 2024, 21: 585-599. PMID: 38627537, DOI: 10.1038/s41575-024-00919-y.Peer-Reviewed Original ResearchLiver cancer managementLiver cancerCancer managementCancer careArtificial intelligenceClinically approved productsInterdisciplinary trainingTumor typesClinical dataClinical trialsPatient managementClinical useCancerPotential of AILiverHidden informationNatural languageIncorporation of AIAI approachesAI systemsPatientsAutomated 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