2025
Vision-language foundation model for generalizable nasal disease diagnosis using unlabeled endoscopic records
Liu X, Gong W, Chen X, Li Z, Liu Y, Wang L, Liu Q, Sun X, Liu X, Chen X, Shi Y, Yu H. Vision-language foundation model for generalizable nasal disease diagnosis using unlabeled endoscopic records. Pattern Recognition 2025, 165: 111646. DOI: 10.1016/j.patcog.2025.111646.BooksLabeled dataGeneralization performanceExpert annotationsArtificial intelligencePre-training datasetSuperior generalization performanceState-of-the-artMedical artificial intelligencePerformance of AI modelsNasal endoscopic imagesLearning frameworkAI modelsMultiple imagesSemantic representationDiagnostic tasksFine-tuningTask-specificUniversal representationDatasetExperimental resultsDisease classificationEndoscopic imagesDiagnosis of diseasesAnnotationFoundation modelArtificial intelligence chatbots as sources for patient education material on child abuse
Nguyen L, Tran V, Li J, Baughn D, Shotwell J, Gushanas K, Hasan S, Falls L, Zhong R. Artificial intelligence chatbots as sources for patient education material on child abuse. Child Protection And Practice 2025, 5: 100167. DOI: 10.1016/j.chipro.2025.100167.Peer-Reviewed Original ResearchNational Child Traumatic Stress NetworkChildhood maltreatmentChild abuseField of psychiatryPatient education materialsInterpersonal traumaPediatric psychologistsPsychiatric disordersChild psychiatristsAbuseReading levelEducational materialsStress networkWord countMaltreatmentActionability of patient education materialsSource of medical informationYears of ageAI chatbotsChildrenArtificial intelligenceNeglectRecommended reading levelChildhoodSecondary outcomesCybersecurity Threats and Mitigation Strategies for Large Language Models in Health Care.
Akinci D'Antonoli T, Tejani A, Khosravi B, Bluethgen C, Busch F, Bressem K, Adams L, Moassefi M, Faghani S, Gichoya J. Cybersecurity Threats and Mitigation Strategies for Large Language Models in Health Care. Radiology Artificial Intelligence 2025, 7: e240739. PMID: 40366259, DOI: 10.1148/ryai.240739.Peer-Reviewed Original ResearchConceptsMalicious actorsLanguage modelArtificial intelligenceRobust security measuresSensitive patient informationProtect patient privacyMalicious attacksUnauthorized manipulationCybersecurity challengesPrivacy breachesCybersecurity threatsCybersecurity risksTraining dataSecurity measuresDeployment stageAI modelsPatient privacyPoisoning dataCybersecurityPrivacyHealth carePatient informationPatient dataImprove medical practiceLanguageComplete AI-Enabled Echocardiography Interpretation With Multitask Deep Learning
Holste G, Oikonomou E, Tokodi M, Kovács A, Wang Z, Khera R. Complete AI-Enabled Echocardiography Interpretation With Multitask Deep Learning. JAMA 2025, 334 PMID: 40549400, PMCID: PMC12186137, DOI: 10.1001/jama.2025.8731.Peer-Reviewed Original ResearchMultitask deep learningAI systemsDiagnostic classification tasksClassification taskDeep learningArtificial intelligenceArea under the receiver operating characteristic curveYale New Haven Health SystemTransthoracic echocardiography studyTransthoracic echocardiographyVentricular systolic dysfunctionParameter estimation taskSystolic dysfunctionDiagnosis tasksEchocardiographic videosRight ventricular systolic dysfunctionLeft ventricular ejection fractionAI predictionsEstimation taskVentricular ejection fractionSevere aortic stenosisManual reportingReceiver operating characteristic curveTaskClinical workflowEmerging Trends in Artificial Intelligence in Neuro-Oncology
Chadha S, Sritharan D, Hager T, D’Souza R, Aneja S. Emerging Trends in Artificial Intelligence in Neuro-Oncology. Current Oncology Reports 2025, 1-12. PMID: 40504358, DOI: 10.1007/s11912-025-01688-w.Peer-Reviewed Original ResearchArtificial intelligenceNeuro-oncologyLeverage natural language processingExtract actionable insightsNatural language processingTreatment response evaluationOptimal treatment planHardware efficiencyLanguage processingComputational pathologyModel generalizabilityActionable insightsAutomated tumor segmentationTumor segmentationRisk stratificationDiagnostic accuracyMolecular classificationTreatment planningClinical reportsComputational techniquesResponse evaluationReviewThis articlePatient outcomesClinical workflowAccelerating drug discoveryArtificial 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 rubricAllocationModelTowards Automating Risk Stratification of Intraductal Papillary Mucinous Neoplasms: Artificial Intelligence Advances Beyond Human Expertise with Confocal Laser Endomicroscopy
Krishna S, Abdelbaki A, Li Z, Culp S, Xiong X, Napoleon B, Mok S, Bertani H, Feng Y, Kongkam P, Luthra A, Machicado J, El-Dika S, Leblanc S, Tan D, Burlen J, Keane M, Keihanian T, Ladd A, Muniraj T, Visrodia K, Chen W, Esnakula A, Hart P, Chao W. Towards Automating Risk Stratification of Intraductal Papillary Mucinous Neoplasms: Artificial Intelligence Advances Beyond Human Expertise with Confocal Laser Endomicroscopy. Pancreatology 2025 PMID: 40447463, DOI: 10.1016/j.pan.2025.05.011.Peer-Reviewed Original ResearchNeedle-based confocal laser endomicroscopyIntraductal papillary mucinous neoplasmBD-IPMNInterobserver agreementArtificial intelligenceConfocal laser endomicroscopyLaser endomicroscopyBranch ductPapillary mucinous neoplasmPerformance of expertsHuman expertiseAI modelsPost Hoc AnalysisMucinous neoplasmsDysplasia gradeEndoscopic ultrasoundClinical criteriaInterobserver variabilityCyst epitheliumSuperior accuracyDysplasiaAUCPost-hocArtificialDiagnostic parametersA Generative Artificial Intelligence Copilot for Biomedical Nanoengineering
Wang Y, Song H, Teng Y, Huang G, Qian J, Wang H, Dong S, Ha J, Ma Y, Chang M, Jeong S, Deng W, Schrank B, Grippin A, Wu A, Edwards J, Zhang Y, Lin Y, Poon W, Wilhelm S, Bi Y, Teng L, Wang Z, Kim B, Jiang W. A Generative Artificial Intelligence Copilot for Biomedical Nanoengineering. ACS Nano 2025, 19: 19394-19407. PMID: 40367350, DOI: 10.1021/acsnano.5c03454.Peer-Reviewed Original ResearchConceptsArtificial intelligenceNatural language processing tasksExtract contextual informationLanguage processing tasksAutomatically extract knowledgeAI-based methodsGenerative artificial intelligenceInformation extractionLanguage modelAutomated learningContextual informationProcessing tasksIntelligent copilotBaseline modelAI toolsDesign tasksTaskQueryScientific queriesAutomaticallyCopilotIntelligenceScientific researchLLMLearningExploring the Use of a Large Language Model in Simulation Debriefing: An Observational Simulation-Based Pilot Study.
Hong E, Kazmir S, Dylik B, Auerbach M, Rosati M, Athanasopoulou S, Himmelstein R, Whitfill T, Johnston L, Wolbrink T, Rosen A, Gross I. Exploring the Use of a Large Language Model in Simulation Debriefing: An Observational Simulation-Based Pilot Study. Simulation In Healthcare The Journal Of The Society For Simulation In Healthcare 2025 PMID: 40326794, DOI: 10.1097/sih.0000000000000861.Peer-Reviewed Original ResearchLanguage modelNASA-TLXTask loadGenerative artificial intelligencePilot studyMean Likert scoreNASA-TLX scoresAI integrationAI technologyArtificial intelligenceHuman oversightTask workloadComprehensive debriefingDebriefing scriptDebriefing qualitySimulation debriefingHigher mental demandComplex taskSimulation facilitatorsSchool of MedicineFacilitator debriefsWorkload assessmentDebriefingSelf-ReportComplex informationArtificial Intelligence in the Management of Heart Failure
Cheema B, Hourmozdi J, Kline A, Ahmad F, Khera R. Artificial Intelligence in the Management of Heart Failure. Journal Of Cardiac Failure 2025 PMID: 40345521, DOI: 10.1016/j.cardfail.2025.02.020.Peer-Reviewed Original ResearchArtificial intelligenceState-of-the-art algorithmsData privacy concernsState-of-the-artManagement of heart failureAI-based toolsElectronic health recordsAI solutionsMultimodal dataHeart failureHealth recordsIntegration challengesHeart failure syndromeStructural heart diseaseHeart failure treatmentIntelligenceImplementation challengesModel performanceModel governanceAdvanced diseaseFailure syndromeCardiomyopathy diagnosisFailure treatmentRisk factorsHeart diseaseEmerging Image-Guided Navigation Techniques for Cardiovascular Interventions: A Scoping Review
Roshanfar M, Salimi M, Jang S, Sinusas A, Kim J, Mosadegh B. Emerging Image-Guided Navigation Techniques for Cardiovascular Interventions: A Scoping Review. Bioengineering 2025, 12: 488. PMID: 40428106, PMCID: PMC12108902, DOI: 10.3390/bioengineering12050488.Peer-Reviewed Original ResearchState-of-the-artCardiac interventionsNavigation techniquesAugmented reality systemReal-time navigationReality systemArtificial intelligenceImage-guided navigationDecision supportOptical coherence tomographyComplex cardiac interventionsState-of-the-art imaging modalitiesReduced procedure timeConventional fluoroscopyImage-guidedProcedure timeCoherence tomographyProcedural outcomesClinical studiesImproved accuracyElectrophysiological interventionsRadiation exposureReal-time guidanceTraditional techniquesImaging modalitiesA Current Review of Generative AI in Medicine: Core Concepts, Applications, and Current Limitations
Rouzrokh P, Khosravi B, Faghani S, Moassefi M, Shariatnia M, Rouzrokh P, Erickson B. A Current Review of Generative AI in Medicine: Core Concepts, Applications, and Current Limitations. Current Reviews In Musculoskeletal Medicine 2025, 18: 246-266. PMID: 40304941, PMCID: PMC12185825, DOI: 10.1007/s12178-025-09961-y.Peer-Reviewed Original ResearchGenerative AIArtificial intelligenceAI modelsSynthetic medical imagesEnhance information retrievalInformation retrievalGenerative artificial intelligenceAI agentsLanguage modelTraining dataModel reasoningComplex workflowsMedical imagesSynthetic dataData typesDecision supportMultiple data typesDiscriminant modelMultimodal modelClinical documentationMedical fieldModel familyEnhanced capabilitiesSpecialized applicationsCore conceptsArtificial Intelligence: Crossing a Threshold in Healthcare Education and Simulation
Bajwa M, Morton A, Patel A, Palaganas J, Gross I. Artificial Intelligence: Crossing a Threshold in Healthcare Education and Simulation. Cureus Journal Of Computer Science 2025, 2: 3758. DOI: 10.7759/s44389-025-03758-3.Peer-Reviewed Original ResearchLeveraging ChatGPT for improved decision-making in interfacility transfers for plastic surgery emergencies based on United States guidelines
Hinson C, Allam O, Glaspy J, Kim T, Ayyala H. Leveraging ChatGPT for improved decision-making in interfacility transfers for plastic surgery emergencies based on United States guidelines. JPRAS Open 2025, 44: 524-528. PMID: 40485859, PMCID: PMC12140855, DOI: 10.1016/j.jpra.2025.04.011.Peer-Reviewed Original ResearchArtificial intelligenceLack of explainabilityFacial traumaInterfacility transferSurgery emergenciesChatGPTAI platformPlastic surgery referralsUnited States guidelinesUpper extremity traumaLow-resource settingsBurden healthcare systemsSurgery referralsFrontline providersImprove decision-makingClinical oversightClinical scenariosEmergency triageSpecialist consultationHealthcare systemPlastic surgeonsU.S. guidelinesExtremity traumaTriage decisionsClinical guidelinesRealism Drives Interpersonal Reciprocity but Yields to AI-Assisted Egocentrism in a Coordination Experiment
Shirado H, Shimizu K, Christakis N, Kasahara S. Realism Drives Interpersonal Reciprocity but Yields to AI-Assisted Egocentrism in a Coordination Experiment. 2025, 1-21. DOI: 10.1145/3706598.3713371.Peer-Reviewed Original ResearchDesign of HCI systemsArtificial intelligenceImproving user performanceVirtual reality technologyHCI systemUser performanceRobot carSocial applicationsEnhance realismEffects of realismVirtual carReality technologyInterpersonal coordinationHuman behaviorPhysical spaceDigital spaceTechnologyIntelligenceCarRealismCommunicationAssistanceGameSpaceCoordinationGenerative Artificial Intelligence in Clinical Medicine and Impact on Gastroenterology
Soroush A, Giuffrè M, Chung S, Shung D. Generative Artificial Intelligence in Clinical Medicine and Impact on Gastroenterology. Gastroenterology 2025 PMID: 40245953, DOI: 10.1053/j.gastro.2025.03.038.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsArtificial intelligenceTraditional machine learning approachesHuman-algorithm interactionsMachine learning approachData privacyGenerative artificial intelligenceAdministrative tasksGenerative AIEndoscopic videosMultiple tasksData modalitiesLearning approachTabular dataOutput reliabilityEffective deploymentInformation flowClinical documentationTaskInformation tasksIntelligenceRelevance to clinical carePotential solutionsSummarizationHealth carePatient educationStrategies to Improve the Robustness and Generalizability of Deep Learning Segmentation and Classification in Neuroimaging
Tran A, Zeevi T, Payabvash S. Strategies to Improve the Robustness and Generalizability of Deep Learning Segmentation and Classification in Neuroimaging. BioMedInformatics 2025, 5: 20. PMID: 40271381, PMCID: PMC12014193, DOI: 10.3390/biomedinformatics5020020.Peer-Reviewed Original ResearchDeep learning modelsGeneralizability of deep learning modelsLearning modelsArtificial intelligenceIntegration of deep learning modelsImprove model robustnessDomain shiftEnhance deep learningTransfer learningData augmentationDeep learningMedical imagesTask-specific applicationsModel robustnessSensitive to artifactsLearning segmentationDeep learning segmentationModel attributesNeuroimaging applicationsRobustnessClassificationDataUncertainty estimationLearningData variabilityArtificial Intelligence for Future Presidents: Teaching AI Literacy to Everyone
Candon K, Georgiou N, Ramnauth R, Cheung J, Fincke E, Scassellati B. Artificial Intelligence for Future Presidents: Teaching AI Literacy to Everyone. Proceedings Of The AAAI Conference On Artificial Intelligence 2025, 39: 28988-28995. DOI: 10.1609/aaai.v39i28.35168.Peer-Reviewed Original ResearchLeveraging Artificial Intelligence to Assess Perceived Age and Donor Facial Resemblance After Face Transplantation
Boroumand S, Gu E, Allam O, Vafa A, Huelsboemer L, Stögner V, Knoedler S, Knoedler L, Klimitz F, Kauke-Navarro M, Haykal S, Pomahac B. Leveraging Artificial Intelligence to Assess Perceived Age and Donor Facial Resemblance After Face Transplantation. Annals Of Plastic Surgery 2025, 94: 468-472. PMID: 40117511, DOI: 10.1097/sap.0000000000004334.Peer-Reviewed Original ResearchConceptsArtificial intelligenceLeverage artificial intelligenceFace transplant patientsVisual analysis softwareFacial analysis softwareSimilarity matchingPostoperative imagingTransplant patientsWilcoxon rank sum testSoftwareRank sum testPatient ageAssessment of perceived ageIntelligenceAllograft ageMatching percentageDonor ageDegree of resemblancePostoperative appearanceMann-WhitneyPatientsFacial transplantationSum testDonor's faceFace transplantation
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