An interpretable machine learning model based on contrast-enhanced CT parameters for predicting treatment response to conventional transarterial chemoembolization in patients with hepatocellular carcinoma
Lu Zhang, Zhe Jin, Chen Li, Zicong He, Bin Zhang, Qiuying Chen, Jingjing You, Xiao Ma, Hui Shen, Fei Wang, Lingeng Wu, Cunwen Ma, Shuixing Zhang
Topics & Concepts
Logistic regressionHepatocellular carcinomaMedicineRandom forestRadiologyStage (stratigraphy)CirrhosisResponse Evaluation Criteria in Solid TumorsContrast (vision)Transcatheter arterial chemoembolizationReceiver operating characteristicDiscriminative modelArtificial intelligenceMachine learningNuclear medicineClinical trialInternal medicineComputer sciencePhases of clinical researchBiologyPaleontologyHepatocellular Carcinoma Treatment and PrognosisRadiomics and Machine Learning in Medical ImagingMRI in cancer diagnosis