Classify multicategory outcome in patients with lung adenocarcinoma using clinical, transcriptomic and clinico-transcriptomic data: machine learning versus multinomial models
Fei Deng, Lanlan Shen, He Wang, Lanjing Zhang
Abstract
associated with dead with disease, respectively, while also inversely linked other outcomes. These cross-linked genes may be used for risk-stratification and future treatment development.
Topics & Concepts
Random forestArtificial intelligenceSupport vector machineProportional hazards modelAdenocarcinomaMultilayer perceptronMultinomial distributionMachine learningLogistic regressionMultinomial logistic regressionOncologyTranscriptomePerceptronInternal medicineOutcome (game theory)MedicineComputer scienceCancerBiologyGeneMathematicsStatisticsArtificial neural networkGene expressionBiochemistryMathematical economicsCancer-related molecular mechanisms researchFerroptosis and cancer prognosisRadiomics and Machine Learning in Medical Imaging