grant
AI-Assisted Microendoscopy for the Early Detection of Esophageal Cancer
Organization BAYLOR COLLEGE OF MEDICINELocation HOUSTON, UNITED STATESPosted 17 Sept 2014Deadline 31 Aug 2028
NIHUS FederalResearch GrantFY2025AI AugmentedAI assistedAI basedAI drivenAI enhancedAI integratedAI poweredAI systemAdoptionAlgorithmic SoftwareAlgorithmic ToolsAlgorithmsAnalAnusApplication ContextAreaArtificial IntelligenceArtificial Intelligence enhancedAugmented by AIAugmented by the AIAugmented with AIAugmented with the AIBiopsyBrazilCOVID-19CV-19Cancer CauseCancer EtiologyCancer HospitalCancersCarcinomaCell NucleusChinaChineseClassificationClinicalClinical ResearchClinical StudyColonComputer AssistedComputer ReasoningComputer softwareComputersCoronavirus Infectious Disease 2019DataData SetDeath RateDetectionDevicesDiagnosisDiagnosticDissemination and ImplementationEarly DiagnosisEastern AfricaEffectivenessEndoscopyEnvironmentEpithelial cancerEpitheliumEsophageal CancerEsophagusEsophagus CancerEthnic OriginEthnicityEvaluationGeographic AreaGeographic LocationsGeographic RegionGeographical LocationGoalsHealth StatusHospitalsImageIncidenceInflammatoryInternationalIranLanguageLevel of HealthMachine IntelligenceMainland ChinaMalignant Epithelial NeoplasmsMalignant Epithelial TumorsMalignant Esophageal NeoplasmMalignant Esophageal TumorMalignant NeoplasmsMalignant TumorMalignant Tumor of the EsophagusMalignant neoplasm of esophagusMicroscopicModelingNeoplasmsNuclearNucleusOptical BiopsyOralParticipantPatientsPerformancePilot ProjectsPopulation HeterogeneityPreventative strategyPrevention strategyPreventive strategyRandomized Controlled Clinical TrialsRandomized, Controlled TrialsResolutionRiskScreening for cancerSensitivity and SpecificitySiteSkinSoftwareSoftware AlgorithmSouth AmericaSpecificitySpeedStomachSystematicsTechnologyTestingTexasTimeTrainingValidationVeterans HospitalsVisualWorkarmartificial intelligence assistedartificial intelligence augmentedartificial intelligence basedartificial intelligence drivenartificial intelligence integratedartificial intelligence poweredautomated algorithmautomatic algorithmcancer preventionchromoendoscopychromoscopyclinical relevanceclinically relevantcomputer aidedcontextual factorscoronavirus disease 2019coronavirus disease-19coronavirus infectious disease-19costdeep learningdeep learning algorithmdeep learning methoddeep learning strategydigitaldiverse populationsearly cancer detectionearly detectionendomicroscopyendomicrosopeendoscopic imagingenhanced with AIenhanced with Artificial Intelligenceepithelial carcinomaesophageal squamous cell neoplasiaexperiencegastricgeographic sitehandheld mobile devicehealth levelhealth literacyheterogeneous populationhigh riskimagingimplementation facilitationimprovedinnovateinnovationinnovativemalignancymicroendoscopemicroendoscopymicroscope imagingmicroscopic imagingmicroscopy imagingmobile devicemortalitymortality ratemortality rationeoplasianeoplasm/cancerneoplasticneoplastic growthoesophageal cancerpatient populationpilot studypilot trialpopulation diversityportabilityrandomized control clinical trialrandomized control trialresolutionsscreeningscreening cancer patientsscreeningssimulationsocio-economicsocio-economicallysocioeconomicallysocioeconomicsstandard of carevalidations
Description preview
Abstract: Esophageal cancer is the 6th most common cause of cancer-related mortality worldwide. While
esophageal squamous cell neoplasia (ESCN) carries a significant global burden, those in certain underserved
geographic regions (South America, eastern Africa, eastern Iran, northern China) have particularly high
incidence and mortality rates due…
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