grant
Shared Resource Core 2: Clinical Artificial Intelligence Core
Organization DANA-FARBER CANCER INSTLocation BOSTON, UNITED STATESPosted 19 Sept 2023Deadline 31 Aug 2028
NIHUS FederalResearch GrantFY2025AI algorithmAI analysisAI basedAI based methodAI based platformAI platformAI systemAcademic TrainingAccelerationAddressAdoptionAdverse Late EffectsAlgorithmic AnalysesAlgorithmic AnalysisAnalyses of AlgorithmsAnalysis of AlgorithmsApacheArtificial IntelligenceArtificial Intelligence platformAssayBioassayBiological AssayCCOPCancer BiologyCancer Research ProgramsCancer Research ProjectCancer TreatmentCancersCharacteristicsChildhood CancersClinicClinicalClinical DataCommunitiesCommunity Clinical Oncology ProgramCommunity OncologyComplexComputer ReasoningComputer softwareComputerized Medical RecordDataData AnalysesData AnalysisData CommonsData ScienceData Science CoreData Science Resource CoreData SetElectronic Medical RecordEnsureGoalsHeterogeneityImageIndustryInformaticsInfrastructureIntelligenceIntratumoral heterogeneityInvestigationInvestmentsKnowledgeLate EffectsMachine IntelligenceMalignant Childhood NeoplasmMalignant Childhood TumorMalignant Neoplasm TherapyMalignant Neoplasm TreatmentMalignant NeoplasmsMalignant Pediatric NeoplasmMalignant Pediatric TumorMalignant TumorMalignant childhood cancerMeasuresMedicalMedical ImagingMedicineMethodsModelingMolecularMultiomic DataNatural Language ProcessingNeuroblastomaPatientsPatternPhenotypePrediction of Radiation ResponsePreparationR-Series Research ProjectsR01 MechanismR01 ProgramRadiationRadiation OncologyRadiation therapyRadiographyRadioresistanceRadiotherapeuticsRadiotherapyReproducibilityResearchResearch GrantsResearch Project GrantsResearch ProjectsResearch ResourcesResearch SupportResource SharingResourcesRoentgenographyScientific Advances and AccomplishmentsSemanticsSoftwareStandardizationTCIATechnologyTextThe Cancer Imaging ArchiveToxic effectToxicitiesTraininganalysis with AIanalysis with artificial intelligenceanalyzed via AIanalyzed via artificial intelligenceanti-cancer researchanti-cancer therapyartificial intelligence algorithmartificial intelligence analysisartificial intelligence basedartificial intelligence methodcancer in a childcancer in childrencancer researchcancer therapycancer-directed therapychild with cancerchildhood malignancychildhood radiationclinical phenotypeclinical translationclinically translatabledata collected in real worlddata interpretationdata streamsexperienceheterogeneity in tumorsimagingimaging biomarkerimaging markerimaging probeimaging-based biological markerimaging-based biomarkerimaging-based markerimprovedintra-tumoral heterogeneityintratumor heterogeneityirradiation responsemalignancymultiomicsmultiple omic datamultiple omicsnatural language understandingneoplasm/canceropen sourcepanomicspediatric cancerpediatric malignancypediatric radiationpreparationsprogramsquantitative imagingradiation during childhoodradiation in childrenradiation resistanceradiation responseradiation treatmentradio resistanceradiological imagingradiomicsreal world dataresponseresponse to radiationresponse to therapyresponse to treatmentscientific accomplishmentsscientific advancessynergismtherapeutic responsetherapy responsetooltreatment responsetreatment responsivenesstreatment with radiationtumortumor heterogeneityusability
Description preview
PROJECT SUMMARY
Artificial intelligence (AI) algorithms have the potential to fundamentally change medicine through their ability to
recognize complex patterns in medical data. The Clinical Artificial Intelligence and Imaging Core (AI Core)
is an essential shared resource that will support the Aims of the Harvard/UCSF ROBIN Research Projects to…
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