2025
AI 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 rubricAllocationModelASHABot: An LLM-Powered Chatbot to Support the Informational Needs of Community Health Workers
Ramjee P, Chhokar M, Sachdeva B, Meena M, Abdullah H, Vashistha A, Nagar R, Jain M. ASHABot: An LLM-Powered Chatbot to Support the Informational Needs of Community Health Workers. 2025, 1-22. DOI: 10.1145/3706598.3713680.Peer-Reviewed Original ResearchCommunity health workersHealth workersInformation needsCommunity health workers’ supervisors,Healthcare servicesHealthcare ecosystemLog analysisMedical knowledgePrivate channelsChatbotSupervisor supportIncreased accountabilityAuthoritative resourcesNeedsSensitive questionsSupervisorsWorkersCommunityInformationDeploymentInterviewsResourcesWorkloadTrainingQuestionsEffects of Robot Competency and Motion Legibility on Human Correction Feedback
Wang S, Wang A, Goncharova S, Scassellati B, Fitzgerald T. Effects of Robot Competency and Motion Legibility on Human Correction Feedback. 2025, 00: 789-799. DOI: 10.1109/hri61500.2025.10974241.Peer-Reviewed Original ResearchCompetent robotsHuman corrective feedbackRobot's interactive behavioursPick-and-place taskLegible motionSupervised robotsUser studyPick-and-placeRobot deploymentHuman feedbackTask objectivesRobotObjective divergenceInteraction behaviorLearningCorrection precisionUsersFeedbackSuboptimal behaviorDeploymentPrecisionLegibilityTaskCorrectionPhysical effortEnvironment scan of generative AI infrastructure for clinical and translational science
Idnay B, Xu Z, Adams W, Adibuzzaman M, Anderson N, Bahroos N, Bell D, Bumgardner C, Campion T, Castro M, Cimino J, Cohen I, Dorr D, Elkin P, Fan J, Ferris T, Foran D, Hanauer D, Hogarth M, Huang K, Kalpathy-Cramer J, Kandpal M, Karnik N, Katoch A, Lai A, Lambert C, Li L, Lindsell C, Liu J, Lu Z, Luo Y, McGarvey P, Mendonca E, Mirhaji P, Murphy S, Osborne J, Paschalidis I, Harris P, Prior F, Shaheen N, Shara N, Sim I, Tachinardi U, Waitman L, Wright R, Zai A, Zheng K, Lee S, Malin B, Natarajan K, Price II W, Zhang R, Zhang Y, Xu H, Bian J, Weng C, Peng Y. Environment scan of generative AI infrastructure for clinical and translational science. Npj Health Systems 2025, 2: 4. PMID: 39872195, PMCID: PMC11762411, DOI: 10.1038/s44401-024-00009-w.Peer-Reviewed Original ResearchInformation technology staffData securityGenerative AIClinician trustTechnology staffAI biasAI infrastructureEnvironment scanningNational Institutes of HealthNational Center for Advancing Translational SciencesComprehensive environmental scanCTSA programInfrastructureTranslational scienceSecurityDeploymentInstitutes of HealthNetworkEnvironmental scanCoordinated approach
2024
Overview of Artificial Intelligence Research Within Hip and Knee Arthroplasty
Mickley J, Kaji E, Khosravi B, Mulford K, Taunton M, Wyles C. Overview of Artificial Intelligence Research Within Hip and Knee Arthroplasty. Arthroplasty Today 2024, 27: 101396. PMID: 39071822, PMCID: PMC11282426, DOI: 10.1016/j.artd.2024.101396.Peer-Reviewed Original ResearchCalibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations
You C, Min Y, Dai W, Sekhon J, Staib L, Duncan J. Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations. 2015 IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 2024, 00: 26140-26150. PMID: 39640960, PMCID: PMC11620289, DOI: 10.1109/cvpr52733.2024.02470.Peer-Reviewed Original ResearchDiverse downstream tasksVision-language modelsPre-trained modelsRepresentation of samplesContrastive learningDownstream tasksFeature reweightingTraining dataFeature patternsModel generalizationGroup annotationsPain pointsGroup labelsAnnotationRobustnessClassifierClipsFeaturesDeepDeploymentBenchmarksTime-intensiveCodeTaskLearningArtificial Intelligence in Cardiovascular Care—Part 2: Applications JACC Review Topic of the Week
Jain S, Elias P, Poterucha T, Randazzo M, Lopez Jimenez F, Khera R, Perez M, Ouyang D, Pirruccello J, Salerno M, Einstein A, Avram R, Tison G, Nadkarni G, Natarajan V, Pierson E, Beecy A, Kumaraiah D, Haggerty C, Avari Silva J, Maddox T. Artificial Intelligence in Cardiovascular Care—Part 2: Applications JACC Review Topic of the Week. Journal Of The American College Of Cardiology 2024, 83: 2487-2496. PMID: 38593945, DOI: 10.1016/j.jacc.2024.03.401.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2023
Comparing 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
2022
RT-Cloud: A cloud-based software framework to simplify and standardize real-time fMRI
Wallace G, Polcyn S, Brooks P, Mennen A, Zhao K, Scotti P, Michelmann S, Li K, Turk-Browne N, Cohen J, Norman K. RT-Cloud: A cloud-based software framework to simplify and standardize real-time fMRI. NeuroImage 2022, 257: 119295. PMID: 35580808, PMCID: PMC9494277, DOI: 10.1016/j.neuroimage.2022.119295.Peer-Reviewed Original ResearchConceptsCloud computingOpen-source Python software packageHigh-performance computingStandardized data formatsBrain Imaging Data Structure (BIDS) standardPython software packageData structure standardsSoftware frameworkOpen standardsData formatLack of standardsHardware requirementsComputingReal timeSoftware packageOpen scienceReal-time fMRIScalabilityTechnical expertiseExecutionDeploymentApplicationsStructure standardsComplexityFormat
2021
The Clinical Engineering–Information Technology Professional Practice Interface
Chartash D, Grout R. The Clinical Engineering–Information Technology Professional Practice Interface. Journal Of Clinical Engineering 2021, 46: 135-140. DOI: 10.1097/jce.0000000000000472.Peer-Reviewed Original ResearchCore taskClinical decision support systemDecision support systemClinical informaticistsSupport systemSystem complexityInformaticsClinical systemsCase studyTaskEngineering designComplexityHierarchical levelsClinical engineeringInformaticistsDeploymentEngineeringSystemDesignEngineersApplied SciencesInterfaceClinical engineersDivideMaximizing the Efficiency of Active Case Finding for SARS-CoV-2 Using Bandit Algorithms
Gonsalves GS, Copple JT, Paltiel AD, Fenichel EP, Bayham J, Abraham M, Kline D, Malloy S, Rayo MF, Zhang N, Faulkner D, Morey DA, Wu F, Thornhill T, Iloglu S, Warren JL. Maximizing the Efficiency of Active Case Finding for SARS-CoV-2 Using Bandit Algorithms. Medical Decision Making 2021, 41: 970-977. PMID: 34120510, PMCID: PMC8484027, DOI: 10.1177/0272989x211021603.Peer-Reviewed Original ResearchConceptsBandit algorithmsMobility dataThompson sampling algorithmWeb appFunctional prototypeTesting resourcesSequential decisionAlgorithmPartial informationSampling algorithmClassic problemDecision scienceSpatial correlationAllocationPoint distanceInformationResourcesDeploymentAppsDecisionsTradeoffHaystackPrototypeObjectsDataChemsearch: collaborative compound libraries with structure-aware browsing
Gaffney S, Smaga S, Schepartz A, Townsend J. Chemsearch: collaborative compound libraries with structure-aware browsing. Bioinformatics Advances 2021, 1: vbab008. PMID: 36700113, PMCID: PMC9710581, DOI: 10.1093/bioadv/vbab008.Peer-Reviewed Original ResearchAccess controlServer applicationsWeb applicationDocker imageSource codeData storageEasy navigationRapid deploymentData filesCompound librariesCompounds of interestChemical compound librariesBrowsingLibraryNavigationSimilar compoundsDeploymentFilesApplicationsStructural propertiesImagesCompoundsImplementationCodeDocumentsChallenges Deploying Robots During a Pandemic
Tsoi N, Connolly J, AdĂ©nĂran E, Hansen A, Pineda K, Adamson T, Thompson S, Ramnauth R, Vázquez M, Scassellati B. Challenges Deploying Robots During a Pandemic. 2021, 234-242. DOI: 10.1145/3434073.3444665.Peer-Reviewed Original ResearchEarly identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules
Shung D, Tsay C, Laine L, Chang D, Li F, Thomas P, Partridge C, Simonov M, Hsiao A, Tay JK, Taylor A. Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules. Journal Of Gastroenterology And Hepatology 2021, 36: 1590-1597. PMID: 33105045, PMCID: PMC11874507, DOI: 10.1111/jgh.15313.Peer-Reviewed Original ResearchConceptsNatural language processingElectronic health recordsLanguage processingNLP algorithmSystematized NomenclatureReal timeAcute gastrointestinal bleedingBidirectional Encoder RepresentationsDecision rulesEHR-based phenotyping algorithmsGastrointestinal bleedingRisk stratification scoresEncoder RepresentationsData elementsPhenotyping algorithmStratification scoresHealth recordsAlgorithmPhenotyping of patientsEmergency department patientsTime of presentationRisk stratification modelED reviewDeploymentExternal validation
2019
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
Campanella G, Hanna M, Geneslaw L, Miraflor A, Werneck Krauss Silva V, Busam K, Brogi E, Reuter V, Klimstra D, Fuchs T. Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nature Medicine 2019, 25: 1301-1309. PMID: 31308507, PMCID: PMC7418463, DOI: 10.1038/s41591-019-0508-1.Peer-Reviewed Original ResearchConceptsDecision support systemWhole slide imagesTrain accurate classification modelsManually annotated datasetDevelopment of decision support systemsSlide imagesPixel-wise manual annotationSupervised deep learningSupport systemAccurate classification modelDeep learning systemComputer decision support systemDeep learningManual annotationData curationClassification modelLearning systemComputational pathologyDatasetDeploymentMetastasis to axillary lymph nodesAxillary lymph nodesBasal cell carcinomaClinical practiceImages
2012
From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported guideline refinement.
Hsueh P, Lan C, Deng V, Zhu X. From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported guideline refinement. 2012, 180: 457-61. PMID: 22874232.Peer-Reviewed Original ResearchConceptsDecision supportData-driven analyticsClinical decision support systemPatient-centric paradigmDecision support systemData-driven frameworkGuideline-based clinical decision support systemPersonalized recommendationsHealthcare domainPersonalization frameworkGuideline refinementCurrent contextPatient-related dataMapping tasksSupport systemDecision problemFrameworkConsequent availabilitySignificant attentionAnalyticsRequirementsStatistical decision problemDeploymentTaskClinical requirements
2011
Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms
Joshi A, Scheinost D, Okuda H, Belhachemi D, Murphy I, Staib LH, Papademetris X. Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms. Neuroinformatics 2011, 9: 69-84. PMID: 21249532, PMCID: PMC3066099, DOI: 10.1007/s12021-010-9092-8.Peer-Reviewed Original ResearchConceptsUser interface controlsUser interfaceNovel object-oriented frameworkCommand-line user interfaceGraphical user interface controlsMedical image analysisObject-oriented frameworkComplex image analysisImage analysisPlatform interoperabilitySoftware objectsReusable componentsInterface controlSource codeSuch algorithmsFramework idealMultiple platformsUnified frameworkAlgorithmRapid developmentDeploymentThorough testingPublic useFrameworkPlatform
2009
Unified framework for development, deployment and testing of image analysis algorithms
Joshi A, Scheinost D, Okuda H, Murphy I, Staib L, Papademetris X. Unified framework for development, deployment and testing of image analysis algorithms. The MIDAS Journal 2009 DOI: 10.54294/pq6gf6.Peer-Reviewed Original ResearchImage analysis algorithmsUser interface controlsUser interfaceAnalysis algorithmCommand-line user interfaceGraphical user interface controlsPlatform interoperabilityInterface controlSource codeComplex algorithmsSuch algorithmsNovel frameworkFramework idealMultiple platformsUnified frameworkAlgorithmRapid developmentDeploymentCustom pipelineImage analysisUsersPublic useFrameworkInteroperabilityDevelopers
2007
An Analysis of Short-Term Responses to Threats of Terrorism
Pinker E. An Analysis of Short-Term Responses to Threats of Terrorism. Management Science 2007, 53: 865-880. DOI: 10.1287/mnsc.1060.0665.Peer-Reviewed Original Research
2005
Overcoming the limitations of integrated clinical digital imaging solutions.
Sinard JH, Mattie ME. Overcoming the limitations of integrated clinical digital imaging solutions. Archives Of Pathology & Laboratory Medicine 2005, 129: 1118-26. PMID: 16119983, DOI: 10.5858/2005-129-1118-otloic.Peer-Reviewed Original ResearchConceptsScalable solutionImaging solutionDigital imagingWork flowImage acquisition stepDigital image acquisitionAnatomic pathology departmentArchiving processGreater usabilityMultiuser environmentNovel solutionAcquisition stepImage acquisitionNumber of photographsSoftwareAdditional flexibilityNumber of advantagesUsabilityMinimal trainingVendorsDeploymentSolutionAdvantagesWidespread acceptanceStorage
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