grant
Explainable Analogical Learning for Oncology Diagnosis and Prediction based on Deep Pathophysiology
NIHUS FederalResearch GrantFY2025AI based modelAI modelAI systemAdoptionAdvanced CancerAdvanced Malignant NeoplasmArchitectureArtificial IntelligenceBig DataBigDataBiological MarkersCancer CauseCancer DetectionCancer EtiologyCancersCaringCategoriesClassificationClinicalClinical Decision Support SystemsCognitiveComplexComputer ReasoningDataData BasesDatabasesDetectionDevelopmentDiagnosisDiagnosticDiseaseDisorderDysfunctionEffectivenessEngineering / ArchitectureEnsureEnvironmentEvolutionFunctional disorderGenerationsGenomicsGlassGoalsHumanInterdisciplinary ResearchInterdisciplinary StudyKnowledgeLearningMachine IntelligenceMachine LearningMalignant NeoplasmsMalignant TumorMetastasisMetastasizeMetastatic LesionMetastatic MassMetastatic NeoplasmMetastatic TumorMethodsModelingModern ManMolecularMultidisciplinary CollaborationMultidisciplinary ResearchNCI OrganizationNational Cancer InstituteNeoplasm MetastasisOncologyOncology CancerPathway interactionsPatientsPerformancePhysiopathologyPredictive Cancer ModelProteomicsPublic HealthRecommendationResearchSafetySamplingSecondary NeoplasmSecondary TumorSeveritiesStudentsSurvival AnalysesSurvival AnalysisSystemSystematicsTechnologyTherapeuticVisualizationartificial intelligence modelartificial intelligence-based modelassess effectivenessbio-markersbiologic markerbiomarkerbiomed informaticsbiomedical informaticscancer carecancer diagnosiscancer metastasiscancer progressioncancer riskcancer survivalcognitive systemcomplex datacomputer based Semantic Analysisdata basedata integrationdeep learningdeep learning methoddeep learning strategydesigndesigningdetermine effectivenessdevelopmentaleffectiveness assessmenteffectiveness evaluationepigenomicsevaluate effectivenessexamine effectivenessgraduate studenthigh dimensionalityimprovedindividual patientindividualized cancer therapymachine based learningmachine learning based methodmachine learning based modelmachine learning methodmachine learning methodologiesmachine learning modelmachine statistical learningmalignancyneoplasm progressionneoplasm/cancerneoplastic progressionnew diagnosticsnew drug treatmentsnew drugsnew markernew pharmacological therapeuticnew therapeuticsnew therapynext generation diagnosticsnext generation therapeuticsnovel biomarkernovel diagnosticsnovel drug treatmentsnovel drugsnovel markernovel pharmaco-therapeuticnovel pharmacological therapeuticnovel therapeuticsnovel therapypathophysiologypathwaypersonalization of treatmentpersonalized cancer therapypersonalized cancer treatmentpersonalized medicinepersonalized therapypersonalized treatmentpetabytepreventpreventingrandom forestrisk stratificationsemantic webstatistical and machine learningstratify risksurvival predictionsynergismtranscriptomicstranslational impacttrustworthinesstumor cell metastasistumor progressionundergradundergraduateundergraduate research experienceundergraduate research opportunitiesundergraduate research programsundergraduate student
Description preview
To improve cancer diagnosis, risk stratification, and therapeutics, the National Cancer Institute has called
for machine learning (ML) methods to mine this heterogeneous Big Data with efficient and interpretable,
but currently unavailable models. Among these, cognitive analogy-based models typically offer superior
interpretability because of their…
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