2025
Artificial intelligence in pediatric intensive care: unlocking integrated monitoring for autonomic nervous system dysregulation
Simms B, Kandil S. Artificial intelligence in pediatric intensive care: unlocking integrated monitoring for autonomic nervous system dysregulation. Pediatric Research 2025, 1-2. PMID: 40437255, DOI: 10.1038/s41390-025-04158-y.Peer-Reviewed Original ResearchAI in Action: A Roadmap from the Radiology AI Council for Effective Model Evaluation and Deployment
Trivedi H, Khosravi B, Gichoya J, Benson L, Dyckman D, Galt J, Howard B, Kikano E, Kunjummen J, Lall N, Li X, Patel S, Safdar N, Salastekar N, Segovis C, van Assen M, Harri P. AI in Action: A Roadmap from the Radiology AI Council for Effective Model Evaluation and Deployment. Journal Of The American College Of Radiology 2025 PMID: 40414408, DOI: 10.1016/j.jacr.2025.05.016.Peer-Reviewed Original ResearchAI modelsArtificial intelligenceIntegration of artificial intelligenceWorkflow implementationRadiology workflowPerformance metricsModel evaluationDevelopment of frameworksResource allocationDeploymentClinical workflowWorkflowStandard processModel performanceReturn on investmentPerformanceIntelligenceEvaluationMetricsComprehensive rubricAllocationModelA comparative analysis of privacy-preserving large language models for automated echocardiography report analysis
Mahmoudi E, Vahdati S, Chao C, Khosravi B, Misra A, Lopez-Jimenez F, Erickson B. A comparative analysis of privacy-preserving large language models for automated echocardiography report analysis. Journal Of The American Medical Informatics Association 2025, 32: 1120-1129. PMID: 40334045, DOI: 10.1093/jamia/ocaf056.Peer-Reviewed Original ResearchConceptsMean square errorLanguage modelLarge modelsHigher accuracyAutomated data extractionClassification metricsNear-perfect performanceGround truthValvular heart diseaseVHD severityIrrelevant informationComputational efficiencyIncreasing processing timeProcessing timeCOTSSmall modelsAccuracyHigh performancePerformanceConsecutive transthoracic echocardiographiesOptimizationRandom reportsTransthoracic echocardiographyRegistry formatMetricsExpert of Experts Verification and Alignment (EVAL) Framework for Large Language Models Safety in Gastroenterology
Giuffrè M, You K, Pang Z, Kresevic S, Chung S, Chen R, Ko Y, Chan C, Saarinen T, Ajcevic M, Crocè L, Garcia-Tsao G, Gralnek I, Sung J, Barkun A, Laine L, Sekhon J, Stadie B, Shung D. Expert of Experts Verification and Alignment (EVAL) Framework for Large Language Models Safety in Gastroenterology. Npj Digital Medicine 2025, 8: 242. PMID: 40319106, PMCID: PMC12049514, DOI: 10.1038/s41746-025-01589-z.Peer-Reviewed Original ResearchReward modelSimilarity-based rankingZero-shot baselineSupervised fine-tuningRejection samplingLanguage modelSimilarity metricModel safetyHuman performanceFine-tuningHuman gradingExpert verificationTime-consumingDecision-makingMedical decision-makingMedical questionsEVALAccuracyLanguageDatasetMetricsAssess accuracyRewardVerificationSetsComputational Phenomapping of Randomized Clinical Trial Participants to Enable Assessment of Their Real-World Representativeness and Personalized Inference
Thangaraj P, Oikonomou E, Dhingra L, Aminorroaya A, Jayaram R, Suchard M, Khera R. Computational Phenomapping of Randomized Clinical Trial Participants to Enable Assessment of Their Real-World Representativeness and Personalized Inference. Circulation Cardiovascular Quality And Outcomes 2025, 18: e011306. PMID: 40261065, PMCID: PMC12203226, DOI: 10.1161/circoutcomes.124.011306.Peer-Reviewed Original ResearchConceptsElectronic health record patientElectronic health recordsDistance metricRandomized clinical trialsElectronic health record dataMachine learning methodsYale New Haven Health SystemElectronic health record cohortRandomized clinical trial participantsLearning methodsHeart failureClinical trial participationTOPCAT participantsReal worldMultidimensional metricRCT participantsHealth recordsTreatment effectsHealth systemCharacteristics of patientsRandomized clinical trial cohortsTrial participantsMetricsUnited StatesNovel statisticEvaluation of navigation and robotic systems for percutaneous image-guided interventions: A novel metric for advanced imaging and artificial intelligence integration
Cornelis F, Filippiadis D, Wiggermann P, Solomon S, Madoff D, Milot L, Bodard S. Evaluation of navigation and robotic systems for percutaneous image-guided interventions: A novel metric for advanced imaging and artificial intelligence integration. Diagnostic And Interventional Imaging 2025, 106: 157-168. PMID: 39884887, DOI: 10.1016/j.diii.2025.01.004.Peer-Reviewed Original ResearchPercutaneous image-guided interventionsArtificial intelligenceRobotic systemImage-guided interventionsNovel metricAdvanced imagingIntegration of advanced imagingArtificial intelligence integrationLevel of automationEvaluation of navigationIntelligent integrationLevel of autonomySurgical robotRobotic devicesNavigationIntegration of imaging technologyNavigation systemNavigation devicesWeb of Science databasesCochrane LibraryIntelligencePRISMA guidelinesAutomationMetricsAggregate score
2024
Bayesian thresholded modeling for integrating brain node and network predictors
Sun Z, Xu W, Li T, Kang J, Alanis-Lobato G, Zhao Y. Bayesian thresholded modeling for integrating brain node and network predictors. Biostatistics 2024, 26: kxae048. PMID: 39780514, PMCID: PMC11823287, DOI: 10.1093/biostatistics/kxae048.Peer-Reviewed Original ResearchConceptsPrediction mechanismNetwork-level metricsExtensive simulationsNetwork predictorPrior modelsSub-networksVector-variantPosterior inferenceNodesSignal patternsPredictable componentBrain nodesSpatial contiguityBayesian regression modelsImagesHierarchyLiterature gapNetworkMetricsCommunicationAlternative approachOut-of-sample predictionsInferenceModelA bibliometric analysis of inflammatory bowel disease research in the Arab world
AlMuhaidib S, Bzeizi K, AlAmeel T, Mosli M, Khoja B, Barakeh D, Alomaim W, Alqahtani S, Al-Bawardy B. A bibliometric analysis of inflammatory bowel disease research in the Arab world. Saudi Journal Of Gastroenterology 2024, 31: 146-156. PMID: 39660608, PMCID: PMC12155454, DOI: 10.4103/sjg.sjg_303_24.Peer-Reviewed Original ResearchCitation impactPublication countsBibliometric analysisResearch outputPrevalence of inflammatory bowel diseaseInflammatory bowel diseaseClarivate AnalyticsIncidence rateResearch impactInstitute for Health MetricsCitationsIncidence trendsHealth metricsIBD incidenceRising prevalenceArab countriesGlobal ratingImproving research impactIBD researchInflammatory bowel disease researchSpearman correlationPrevalenceClarivateMetricsOutputLong-Axial Field-Of-View Limited-Angle PET System with Ultra-High Time-Of-Flight and Depth-Of-Interaction
Marin T, Chemli Y, Razdevšek G, Zhuo Y, Orehar M, Najmaoui Y, Dolenec R, Gascon D, Gola A, Benlloch J, Alamo J, Barbera J, Fernandez-Tenllado J, Gomez S, Korpar S, Krizan P, Majewski S, Manera R, Mariscal-Castilla A, Mauricio J, Merzi S, Morera C, Pavon G, Pavon N, Penna M, Seljak A, Studen A, Zontar D, Pestotnik R, Fakhri G. Long-Axial Field-Of-View Limited-Angle PET System with Ultra-High Time-Of-Flight and Depth-Of-Interaction. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10658297.Peer-Reviewed Original ResearchDepth of interactionDepth-of-interaction resolutionTime-of-flightPET systemImage quality metricsTime-of-flight resolutionField-of-view scanningSacrificing image qualityQuality metricsSilicon photomultipliersDetector panelPET instrumentationImage qualityResolution systemAngle geometryGeometric correctionReduce costsPerformancePhotomultiplierSystemResolutionMetricsElectronReflections on inductive thematic saturation as a potential metric for measuring the validity of an inductive thematic analysis with LLMs
De Paoli S, Mathis W. Reflections on inductive thematic saturation as a potential metric for measuring the validity of an inductive thematic analysis with LLMs. Quality & Quantity 2024, 59: 683-709. DOI: 10.1007/s11135-024-01950-6.Peer-Reviewed Original ResearchA FAIR, open-source virtual reality platform for dendritic spine analysis
Reimer M, Kauer S, Benson C, King J, Patwa S, Feng S, Estacion M, Bangalore L, Waxman S, Tan A. A FAIR, open-source virtual reality platform for dendritic spine analysis. Patterns 2024, 5: 101041. PMID: 39568639, PMCID: PMC11573899, DOI: 10.1016/j.patter.2024.101041.Peer-Reviewed Original ResearchVirtual realityVirtual reality platformSoftware ecosystemReality platformData standardSuperior accuracyDatasetWorkflowValidation processDendritic spine morphologySpine analysisDendritic spinesReconstruction techniqueSpine lengthMethod's superior accuracyDendritic spine lengthSpine morphologyMetricsMorphological metricsNeurodataFairnessBiomedical blockchain with practical implementations and quantitative evaluations: a systematic review
Lacson R, Yu Y, Kuo T, Ohno-Machado L. Biomedical blockchain with practical implementations and quantitative evaluations: a systematic review. Journal Of The American Medical Informatics Association 2024, 31: 1423-1435. PMID: 38726710, PMCID: PMC11105130, DOI: 10.1093/jamia/ocae084.Peer-Reviewed Original ResearchConceptsElectronic health recordsSystematic reviewData sharingMedical data sharingSpeed metricsPreferred Reporting ItemsCertificate storageDecentralized InternetNetwork permissionsBlockchain platformBlockchain applicationsEvaluation metricsBiomedical domainBlockchainBiomedical data managementHealth recordsData managementData storageReporting ItemsHealth sectorQuantitative metricsMedical facilitiesMetricsTrial managementClinical trial managementA Unified Approach for Synthesizing Multimodal Brain MR Images via Gated Hybrid Fusion
Cho J, Liu X, Xing F, Ouyang J, El Fakhri G, Park J, Woo J. A Unified Approach for Synthesizing Multimodal Brain MR Images via Gated Hybrid Fusion. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2024 DOI: 10.58530/2024/2242.Peer-Reviewed Original ResearchGPT-4 Performance for Neurologic Localization
Lee J, Choi E, McDougal R, Lytton W. GPT-4 Performance for Neurologic Localization. Neurology Clinical Practice 2024, 14: e200293. PMID: 38596779, PMCID: PMC11003355, DOI: 10.1212/cpj.0000000000200293.Peer-Reviewed Original ResearchGenerative Pretrained TransformerText classificationText datasetsClass labelsPretrained TransformerLanguage modelF1 scorePerformance metricsKnowledge baseMetricsInadequate knowledge baseClassificationReduce health care disparitiesClinical reasoningCapabilityPerformanceTextHealth care disparitiesDatasetSoftwareOptimized Multilayer Perceptron for Sensorimotor Functional Mapping Based on a Few Minutes of Intracranial Electroencephalogram Data
Iktimal A, Spencer D, Alkawadri R. Optimized Multilayer Perceptron for Sensorimotor Functional Mapping Based on a Few Minutes of Intracranial Electroencephalogram Data. Annals Of Neurology 2024, 96: 187-193. PMID: 38506405, DOI: 10.1002/ana.26915.Peer-Reviewed Original ResearchMultilayer perceptronTanh activation functionArea under the curveMultilayer Perceptron performanceOptimal multilayer perceptronImbalanced dataF1 scoreFeature extensionNeural networkActivation functionElectroencephalogram-dataSensorimotor cortexIntractable epilepsy patientsPerceptronCentral sulcusCross-validationAnterior lipEpilepsy patientsGaussian distribution functionFunctional mappingNetworkMetricsIntra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer’s Disease and Cognitive Impairment
Kolla S, Falakshahi H, Abrol A, Fu Z, Calhoun V. Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer’s Disease and Cognitive Impairment. Sensors 2024, 24: 814. PMID: 38339531, PMCID: PMC10857295, DOI: 10.3390/s24030814.Peer-Reviewed Original ResearchConceptsGraph metricsFunctional network connectivityIndependent component analysisResting state fMRI dataData-driven methodologyNetwork connectivityNovel metricFunctional nodesNode sizeNodesLocal graph metricsMetricsNode dimensionsGraphAlzheimer's diseaseMild cognitive impairmentNetwork neuroscienceNeuroimaging researchNeuroimaging investigationsExpert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation.
Hoebel K, Bridge C, Ahmed S, Akintola O, Chung C, Huang R, Johnson J, Kim A, Ly K, Chang K, Patel J, Pinho M, Batchelor T, Rosen B, Gerstner E, Kalpathy-Cramer J. Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation. Radiology Artificial Intelligence 2024, 6: e220231. PMID: 38197800, PMCID: PMC10831514, DOI: 10.1148/ryai.220231.Peer-Reviewed Original ResearchConceptsBrain tumor segmentationDeep learning algorithmsSegmentation qualityLearning algorithmsTumor segmentationBrain tumor segmentation algorithmQuantitative quality metricsTumor segmentation algorithmClinical expert evaluationSegmentation performanceAlgorithm evaluationSegmentation algorithmQuality metricsDice scoreHausdorff distanceSegmentation casesAlgorithmExperimental resultsExpert evaluationQuality evaluationMetricsSurvey article
2023
Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces
Wang X, Zhu J, Pan W, Zhu J, Zhang H. Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces. Journal Of The American Statistical Association 2023, 119: 2772-2784. PMID: 40078669, PMCID: PMC11902916, DOI: 10.1080/01621459.2023.2277417.Peer-Reviewed Original ResearchMetric spaceStatistical inferenceGlivenko-CantelliCorrespondence theoremEuclidean spaceGlivenko-Cantelli theoremDistribution functionNonparametric statistical inferenceDonsker propertyProbability measuresGeneral spaceRandom objectsTheoremMeasurement theorySupplementary materialsEuclideanSpaceIndependence testInferenceDonskerCorrespondenceNonparametricHypercubeMetricsFunctionIntroducing Explicit Gaze Constraints to Face Swapping
Wilson E, Shic F, Jain E. Introducing Explicit Gaze Constraints to Face Swapping. 2023, 1-7. DOI: 10.1145/3588015.3588416.Peer-Reviewed Original ResearchFace swapsHuman-computer interactionNovel loss functionComputer interactionFace SwappingTraining dataLoss functionLoss metricsSynthetic facesEye regionFace identityFull faceClassifierAttributesGazeSwappingDetection effortsEntertainmentMetricsClassificationTechnologyConstraintsNaturalnessApplicationsMethodComparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation
Avesta A, Hossain S, Lin M, Aboian M, Krumholz H, Aneja S. Comparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation. Bioengineering 2023, 10: 181. PMID: 36829675, PMCID: PMC9952534, DOI: 10.3390/bioengineering10020181.Peer-Reviewed Original ResearchLimited training dataDice scoreComputational memoryTraining dataBrain imagesDeep-learning methodsHigher Dice scoresSegmentation accuracyAuto-segmentation modelComputational speedPerformance metricsOne-sliceAuto-SegmentationBetter performanceConsecutive slicesImagesDeploymentLowest Dice scoresMemoryPerformanceTrainingMetricsModelAccuracyData
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