Zhangsheng Yu
Professor Adjunct of BiostatisticsCards
About
Research
Publications
2025
Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST
Gong Y, Yuan X, Jiao Q, Yu Z. Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST. Nature Communications 2025, 16: 3977. PMID: 40295488, PMCID: PMC12037780, DOI: 10.1038/s41467-025-59139-w.Peer-Reviewed Original ResearchConceptsGene expression signalsSpatial transcriptomics data analysisExpression signalsTranscriptome data analysisHeterogeneous graph networkReal-world datasetsSpatial expression patternsOver-smoothing problemSpatial transcriptomics dataGlobal spatial relationshipsST data analysisTranscriptome dataUltra-large-scaleConquer strategyExpression patternsGraph networkData splittingGenesIncreased diagnostic accuracy and better morphology characterization of unruptured intracranial aneurysm by ultra-high-resolution photon-counting detector CT angiography
He N, Lyu H, Zhang Y, Li R, Xu Z, Haacke E, Cui Y, Li J, Dong H, Han W, Chang R, Hu Z, Zhu C, Yu Z, Lu Y, Jiang H, Yan F. Increased diagnostic accuracy and better morphology characterization of unruptured intracranial aneurysm by ultra-high-resolution photon-counting detector CT angiography. Journal Of NeuroInterventional Surgery 2025, jnis-2025-023094. PMID: 40185624, DOI: 10.1136/jnis-2025-023094.Peer-Reviewed Original ResearchDigital subtraction angiographyUnruptured intracranial aneurysmsPer-aneurysm basisDiagnostic accuracyInter-rater agreementIntracranial aneurysmsIncrease diagnostic accuracyUIA managementCT angiographyProspective studyCerebral vascular diseaseSubtraction angiographyPatient managementWall calcificationPer-vesselAneurysmAngiographyVascular diseaseMorphological evaluationAneurysm irregularityUHRDetect unruptured intracranial aneurysmsUltra-high-resolution (UHRHypointensityReconstructed imagesA 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 diagnosisIntelligenceGuidelines for the diagnosis and treatment of depressive disorders by integrating Chinese and Western medicine (English edition)
Liu L, Wang J, Li W, Gao J, Li W, Li Y, Luo L, Guo L, Hu Y, Chen Y, Chen H, Yu L, Fen B, Jia H, Zhang Z, Yan Z, Chen W, Yu Z, Wang Z. Guidelines for the diagnosis and treatment of depressive disorders by integrating Chinese and Western medicine (English edition). General Psychiatry 2025, 38: e101747. PMID: 39944776, PMCID: PMC11815422, DOI: 10.1136/gpsych-2024-101747.Peer-Reviewed Original Research
2024
Thorny but rosy: prosperities and difficulties in ‘AI plus medicine’ concerning data collection, model construction and clinical deployment
Xia Y, Yu Z. Thorny but rosy: prosperities and difficulties in ‘AI plus medicine’ concerning data collection, model construction and clinical deployment. General Psychiatry 2024, 37: e101436. PMID: 39717668, PMCID: PMC11664349, DOI: 10.1136/gpsych-2023-101436.Peer-Reviewed Original ResearchDeep learning for oncologic treatment outcomes and endpoints evaluation from CT scans in liver cancer
Xia Y, Zhou J, Xun X, Johnston L, Wei T, Gao R, Zhang Y, Reddy B, Liu C, Kim G, Zhang J, Zhao S, Yu Z. Deep learning for oncologic treatment outcomes and endpoints evaluation from CT scans in liver cancer. Npj Precision Oncology 2024, 8: 263. PMID: 39551847, PMCID: PMC11570623, DOI: 10.1038/s41698-024-00754-z.Peer-Reviewed Original ResearchProgression-free survivalCT scanLiver cancerAccurate treatment response assessmentResponse evaluationMetastatic organ sitesOncological treatment outcomesResponse Evaluation CriteriaLow-risk patientsTreatment response assessmentTreatment response evaluationTreatment response classificationAdvanced liver cancerStratify high-riskMultifocal hepatic lesionsTreatment outcome assessmentEvaluation of responseOverall survivalEvaluation CriteriaInternal five-fold cross-validationOncology clinical trialsResponse assessmentSolid tumorsClinical trialsTreatment outcomesMediation analysis in longitudinal study with high-dimensional methylation mediators
Cui Y, Lin Q, Yuan X, Jiang F, Ma S, Yu Z. Mediation analysis in longitudinal study with high-dimensional methylation mediators. Briefings In Bioinformatics 2024, 25: bbae496. PMID: 39406521, PMCID: PMC11479716, DOI: 10.1093/bib/bbae496.Peer-Reviewed Original ResearchConceptsBody mass indexMediation analysisPaternal body mass indexGeneralized estimating equationsLinear mixed-effects modelsCohort dataMass indexMixed-effects modelsDNA methylation sitesHigh-dimensional mediation analysisLongitudinal studyBonferroni correctionAccurate parameter estimatesSobel testVariable selectionLongitudinal dataSimulation studyIndependence screeningMethylation sitesCpG sitesIndirect effectsParameter estimationLinearization methodHypothesis testingCT-based multimodal deep learning for non-invasive overall survival prediction in advanced hepatocellular carcinoma patients treated with immunotherapy
Xia Y, Zhou J, Xun X, Zhang J, Wei T, Gao R, Reddy B, Liu C, Kim G, Yu Z. CT-based multimodal deep learning for non-invasive overall survival prediction in advanced hepatocellular carcinoma patients treated with immunotherapy. Insights Into Imaging 2024, 15: 214. PMID: 39186192, PMCID: PMC11347550, DOI: 10.1186/s13244-024-01784-8.Peer-Reviewed Original ResearchConvolutional-recurrent neural networkAdvanced hepatocellular carcinomaSpatial-temporal informationHepatocellular carcinomaCT scanOverall survival predictionRECIST criteriaClinical variablesPatients treated with immunotherapyExtract spatial-temporal informationFollow-up CT imagesPrognostic modelAdvanced HCC patientsRisk group stratificationDeep learning-based modelTest setDisease statusMethodsThis retrospective studyLog-rank testMultimodal deep learningMulti-modal inputsSurvival predictionDeep learning modelsAnalysis of CT scansPatient's disease statusHEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics
Yuan X, Ma Y, Gao R, Cui S, Wang Y, Fa B, Ma S, Wei T, Ma S, Yu Z. HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics. Nature Communications 2024, 15: 5700. PMID: 38972896, PMCID: PMC11228050, DOI: 10.1038/s41467-024-49846-1.Peer-Reviewed Original ResearchConceptsSpatially variable genesVariable genesSpatial expression patternsSpatial transcriptomics technologiesSpatial transcriptomics researchTranscriptome researchTranscriptomic technologiesBiological functionsExpression patternsSpatial transcriptomicsGenesState-of-the-art methodsColorectal cancer dataIssues and Solutions in Psychiatric Clinical Trial with Case Studies
Chen X, Chen J, Zhao X, Mu R, Tan H, Yu Z. Issues and Solutions in Psychiatric Clinical Trial with Case Studies. Neuropsychiatric Disease And Treatment 2024, 20: 1191-1200. PMID: 38855383, PMCID: PMC11162181, DOI: 10.2147/ndt.s454813.Peer-Reviewed Original ResearchMental disordersFeatures of mental disordersPsychiatric clinical trialsTreat mental disordersMental health servicesAnxiety disordersSymptom presentationLongitudinal designRating ScaleDiverse sampleDisorder progressionResearch criteriaMental diseasesClinical interventionsDependability of findingsHistory gatheringDisordersClinical researchHealth servicesPsychotherapyDiagnosing mental diseaseSample representativePsychiatricAnxietyPsychiatrists