grant

Informatics strategies to improve immune-related adverse event detection in cancer patients

Organization BRIGHAM AND WOMEN'S HOSPITALLocation BOSTON, UNITED STATESPosted 1 Sept 2024Deadline 31 Aug 2029
NIHUS FederalResearch GrantFY2025AI language modelsAI systemAI technologyAchievementAchievement AttainmentActive Follow-upAddressAdverse ExperienceAdverse eventArtificial IntelligenceAttentionAutoimmuneBiomedical ResearchBostonCTCAECancer DetectionCancer PatientCancer Surveillance ResearchCancer SurvivorshipCancersCaringCheckpoint inhibitorClassificationClinicalClinical ResearchClinical StudyClinical TrialsCommon Terminology Criteria for Adverse EventsCommon Toxicity CriteriaComputer ReasoningComputersDF/HCCDana-Farber Cancer InstituteDataData BasesData CollectionData SetDatabasesDetectionDevelopmentDiagnosisDiagnosticEffectivenessElectronic Health RecordEligibilityEligibility DeterminationEnrollmentEnvironmentGeneral PractitionersGeneralistsGenerationsGoalsHIPAAHealth Insurance Portability and Accountability ActHospitalsHumanImmune MonitoringImmune checkpoint inhibitorImmune systemImmunologic MonitoringImmunological MonitoringImmunomonitoringImpairmentInflammatoryInformaticsInformation RetrievalInformation extractionInvestigationInvestigatorsKennedy Kassebaum ActKnowledgeLabelLanguageLanguage DevelopmentMachine IntelligenceMalignant NeoplasmsMalignant TumorManualsMeasuresMethodsModelingModern ManMonitorMorbidityMorbidity - disease rateNatural Language ProcessingOutputPL 104-191PL104-191PathologyPathway interactionsPatient MonitoringPatientsPerformancePhenotypePhysiciansProcessPrognosisProtocol ScreeningPublic Law 104-191QOLQOL improvementQuality of lifeRandomized, Controlled TrialsReportingResearch PersonnelResearchersRetrievalRhode IslandRisk FactorsSeveritiesStandardizationSystemSystematicsTechnologyTextTransformer language modelTranslatingUnited States Health Insurance Portability and Accountability ActValidationWorkacquiring language skillsactive followupadverse event monitoringartificial intelligence language modelsartificial intelligence technologybiobankbiorepositorycancer carecancer survivalclinical applicabilityclinical applicationclinical careclinical phenotypeclinical significanceclinical translationclinical trial enrollmentclinical validationclinically significantclinically translatablecomputer scientistcostdata basedata collected in real worlddata formatdata standardizationdata standardsdata streamsdeep learningdeep learning based modeldeep learning methoddeep learning modeldeep learning strategydesigndesigningdevelopmentalelectronic health care recordelectronic health medical recordelectronic health plan recordelectronic health registryelectronic medical health recordelectronic structureenrollfollow upfollow-upfollowed upfollowupimmune check point inhibitorimmune-mediated adverse eventsimmune-related adverse effectimmune-related adverse eventsimmune-related adverse reactionimprovedimprovements in QOLimprovements in quality of lifeinnovateinnovationinnovativeinsightinteroperabilitylanguage acquisitionlanguage learninglanguage traininglarge language modellarge scale language modelmalignancymassive scale language modelsmultidisciplinarynatural language understandingneoplasm/cancerneuralnovelpathwaypharmacovigilancepre-trained modelprospectivequality of life improvementrandomized control trialreal world datareal world evidencestructured datasurvivorshipsynthetic datatumorunstructured datausabilityvalidations
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PROJECT SUMMARY/ABSTRACT
Immune checkpoint inhibitors (ICIs) have drastically improved cancer survival over the past decade, but this

survival comes at the cost of a new class of immune-related adverse events (irAEs) characterized by

inflammatory and auto-immune pathologies that occur and persist long after ICI discontinuation. These irAEs

can…

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Informatics strategies to improve immune-related adverse event detection in cancer patients — BRIGHAM AND WOMEN'S HOSPIT | Dev Procure