2025
A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images
Yang Z, Wei T, Liang Y, Yuan X, Gao R, Xia Y, Zhou J, Zhang Y, Yu Z. A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images. Nature Communications 2025, 16: 2366. PMID: 40064883, PMCID: PMC11894166, DOI: 10.1038/s41467-025-57587-y.Peer-Reviewed Original ResearchConceptsWhole slide imagesLeveraging self-supervised learningScarcity of annotated dataHistopathological imagesSelf-supervised learningPre-training approachSelf-supervised modelPre-trained modelsApplication of artificial intelligenceSmall-scale dataIntelligent healthcareEnhance model performanceExpert annotationsPre-trainingArtificial intelligenceComputational pathologyImaging modelEfficient solutionSlide imagesCancer classificationModel performanceRepresentationImagesCancer diagnosisIntelligence
2015
Classification of Cancer Primary Sites Using Machine Learning and Somatic Mutations
Chen Y, Sun J, Huang L, Xu H, Zhao Z. Classification of Cancer Primary Sites Using Machine Learning and Somatic Mutations. BioMed Research International 2015, 2015: 491502. PMID: 26539502, PMCID: PMC4619847, DOI: 10.1155/2015/491502.Peer-Reviewed Original ResearchConceptsMachine learningF-measureAvailable big dataSupport vector machineBig dataVector machineClassification experimentsAccurate classificationCancer classificationGene function informationMachineSomatic mutation informationClassificationMutation informationFunction informationLearningGene symbolsInformationGene featuresGreat opportunityPerformanceSomatic mutation dataMutation dataAccuracyPrediction
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