2023
Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions
Samant S, Bakhos J, Wu W, Zhao S, Kassab G, Khan B, Panagopoulos A, Makadia J, Oguz U, Banga A, Fayaz M, Glass W, Chiastra C, Burzotta F, LaDisa J, Iaizzo P, Murasato Y, Dubini G, Migliavacca F, Mickley T, Bicek A, Fontana J, West N, Mortier P, Boyers P, Gold J, Anderson D, Tcheng J, Windle J, Samady H, Jaffer F, Desai N, Lansky A, Mena-Hurtado C, Abbott D, Brilakis E, Lassen J, Louvard Y, Stankovic G, Serruys P, Velazquez E, Elias P, Bhatt D, Dangas G, Chatzizisis Y. Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions. JACC Cardiovascular Interventions 2023, 16: 2479-2497. PMID: 37879802, DOI: 10.1016/j.jcin.2023.07.022.Peer-Reviewed Original ResearchConceptsArtificial intelligenceExtended realityVirtual clinical trialsComputer scientistsComputational technologiesIntelligenceMedical technology innovatorsTechnology innovatorsComputational simulationsTechnologyRealityApplicationsBiomedical engineersBioinformaticsSimulationsDevice industryVisualizationConstraintsEngineersExpertsRecent advancesPlanningObstaclesPO83 Utilization of a Virtual Clinical Trial to Characterize Sensitivity of the Linear-Quadratic Model
Tien C, Draeger E, Guan F, Carlson D, Chen Z. PO83 Utilization of a Virtual Clinical Trial to Characterize Sensitivity of the Linear-Quadratic Model. Brachytherapy 2023, 22: s110. DOI: 10.1016/j.brachy.2023.06.184.Peer-Reviewed Original ResearchTumor control probabilityClinical trialsLinear-quadratic modelNumber of patientsPatient cohort sizeTCP curvesRadiobiological parametersVirtual clinical trialsGy-1Cohort sizeRange of dosesPatient outcomesReference cohortPatientsHeterogeneous cohortVirtual patientsNew trialsRadiobiological parameter valuesClonogenic populationPatient ordersControl probabilityGyInput model parametersTrialsCohortDigital Twins for Radiation Oncology
Jensen J, Deng J. Digital Twins for Radiation Oncology. 2023, 989-993. DOI: 10.1145/3543873.3587688.Peer-Reviewed Original ResearchDigital twin technologyDigital twinTwin technologyDigital twin networkModern cryptographic techniquesClinical decision-making supportDecision-making supportCryptographic techniquesVirtual clinical trialsTwin networkConventional machineGeneralized architectureFuture scientific advancesNatural applicationModeling techniquesPatient dataTechnologyMultiple institutionsLarge numberArchitectureMachineMultiscale modeling techniqueNetworkApplicationsTechnique
2018
Improved discrimination between benign and malignant LDCT screening-detected lung nodules with dynamic over static 18F-FDG PET as a function of injected dose
Ye Q, Wu J, Lu Y, Naganawa M, Gallezot JD, Ma T, Liu Y, Tanoue L, Detterbeck F, Blasberg J, Chen MK, Casey M, Carson RE, Liu C. Improved discrimination between benign and malignant LDCT screening-detected lung nodules with dynamic over static 18F-FDG PET as a function of injected dose. Physics In Medicine And Biology 2018, 63: 175015. PMID: 30095083, PMCID: PMC6158045, DOI: 10.1088/1361-6560/aad97f.Peer-Reviewed Original ResearchConceptsPopulation-based input functionStandardized uptake valueImage-derived input functionLung nodulesClinical trialsTime-activity curvesLow-dose computed tomography (LDCT) screeningLung cancer mortality ratesIndeterminate lung nodulesComputed Tomography ScreeningF-FDG PETCancer mortality ratesStatic PET acquisitionVirtual clinical trialsScan durationTomography screeningFDG injectionPET scansMortality rateUptake valueAccurate diagnosisMalignant lung nodulesROC analysisPatient dataMalignant nodules
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