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 ResearchA 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 researchLLMLearningArtificial 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 diseaseRealism 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 educationArtificial 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 transplantationA foundation model for generalizable cancer diagnosis and survival prediction from histopathological images
Yang Z, Wei T, Liang Y, Yuan X, Gao R, Xia Y, Zhou J, Zhang Y, Yu Z. A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images. Nature Communications 2025, 16: 2366. PMID: 40064883, PMCID: PMC11894166, DOI: 10.1038/s41467-025-57587-y.Peer-Reviewed Original ResearchConceptsWhole slide imagesLeveraging self-supervised learningScarcity of annotated dataHistopathological imagesSelf-supervised learningPre-training approachSelf-supervised modelPre-trained modelsApplication of artificial intelligenceSmall-scale dataIntelligent healthcareEnhance model performanceExpert annotationsPre-trainingArtificial intelligenceComputational pathologyImaging modelEfficient solutionSlide imagesCancer classificationModel performanceRepresentationImagesCancer diagnosisIntelligenceHigh Verbal Intelligence in Juvenile Delinquents: Protective or Risk Factor?
Garcia J, Mattuck S, Kovalenko J, Li N, Shelton M, Quintana D, Grigorenko E. High Verbal Intelligence in Juvenile Delinquents: Protective or Risk Factor? Youth Justice 2025 DOI: 10.1177/14732254251316857.Peer-Reviewed Original ResearchRisk factors of delinquencyFactors of delinquencyJuvenile delinquencyDetained youthDelinquencyVerbal intelligenceJIYProtective factorsYouthOffensesVerbal intelligence quotientAcademic achievement scoresAcademic achievement testFuture behaviorIntelligence quotientJuvenilesAchievement scoresAchievement testGenderRace/ethnicityIntelligenceImportant risk factorsEvaluation 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 scoreLeveraging Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism
Mojibian H, Khosla A. Leveraging Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism. 2025, 1-15. DOI: 10.1007/978-3-030-70904-4_72-1.Peer-Reviewed Original ResearchThe Promise of Artificial Intelligence and Machine Learning in Geriatric Anesthesiology Education: An Idea Whose Time Has Come
Chu L, Kurup V. The Promise of Artificial Intelligence and Machine Learning in Geriatric Anesthesiology Education: An Idea Whose Time Has Come. Current Anesthesiology Reports 2025, 15: 15. DOI: 10.1007/s40140-024-00660-x.Peer-Reviewed Original ResearchMachine learningArtificial intelligenceIntegration of AIPotential of artificial intelligenceData-driven decision-makingAnesthesia educationEra of digital transformationPersonalized learning experienceAI capabilitiesPrecision learningHuman expertiseAI integrationCollaborative environmentAdaptive learning moduleAI simulationReal-time feedbackContinuing professional developmentLearning moduleDigital transformationProfessional developmentLearning experienceLearningEducationEnhance proficiencyIntelligence
2024
Brain networks and intelligence: A graph neural network based approach to resting state fMRI data
Thapaliya B, Akbas E, Chen J, Sapkota R, Ray B, Suresh P, Calhoun V, Liu J. Brain networks and intelligence: A graph neural network based approach to resting state fMRI data. Medical Image Analysis 2024, 101: 103433. PMID: 39708510, PMCID: PMC11877132, DOI: 10.1016/j.media.2024.103433.Peer-Reviewed Original ResearchConceptsGraph neural networksNeural networkGraph isomorphism networkGraph convolutional layersGraph convolutional networkMachine learning modelsNetwork connectivity matrixCognitive processesConvolutional layersConvolutional networkPrediction taskModel architectureGraph architectureAdolescent Brain Cognitive Development datasetResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingLearning modelsMiddle frontal gyrusPredicting individual differencesResting state fMRI dataPredictive intelligenceIntelligenceNetworkFunctional network connectivity matricesArchitectureApplication of digital tools and artificial intelligence in the Myasthenia Gravis Core Examination
Garbey M, Lesport Q, Girma H, Öztosun G, Abu-Rub M, Guidon A, Juel V, Nowak R, Soliven B, Aban I, Kaminski H. Application of digital tools and artificial intelligence in the Myasthenia Gravis Core Examination. Frontiers In Neurology 2024, 15: 1474884. PMID: 39697445, PMCID: PMC11652356, DOI: 10.3389/fneur.2024.1474884.Peer-Reviewed Original ResearchNatural language processingMyasthenia gravisArtificial intelligenceArtificial intelligence methodsSeries of algorithmsComputer visionSignal processing methodsExamination of patientsConventional clinical settingsLanguage processingIntelligence methodsNon-physician healthcare providersVideoControl subjectsClinical trialsPatientsRespiratory metricsMyastheniaBreath countClinical settingAlgorithmBody motionVideos of patientsTelemedicine evaluationIntelligenceArtificial Intelligence in IVF Laboratories: Elevating Outcomes Through Precision and Efficiency
Hew Y, Kutuk D, Duzcu T, Ergun Y, Basar M. Artificial Intelligence in IVF Laboratories: Elevating Outcomes Through Precision and Efficiency. Biology 2024, 13: 988. PMID: 39765654, PMCID: PMC11727220, DOI: 10.3390/biology13120988.Peer-Reviewed Original ResearchArtificial intelligenceIn vitro fertilizationPattern recognition capabilitiesHuman-machine interfaceData securityReducing human errorIn vitro fertilization laboratoryDeep learningNeural networkMachine learningAI technologyAlgorithmic biasRecognition capabilityReproductive medicineHuman errorSperm selectionEffects of AIStandard processIntelligenceIncreased accuracySensitivity fieldPersonalized treatment plansQuality assuranceOperational efficiencyLearningArtificial Intelligence in Diagnosing and Managing Vascular Surgery Patients: An Experimental Study Using the GPT-4 Model
Alexiou V, Sumpio B, Vassiliou A, Kakkos S, Geroulakos G. Artificial Intelligence in Diagnosing and Managing Vascular Surgery Patients: An Experimental Study Using the GPT-4 Model. Annals Of Vascular Surgery 2024, 111: 260-267. PMID: 39586530, DOI: 10.1016/j.avsg.2024.11.014.Peer-Reviewed Original ResearchNatural language processingAI modelsArtificial intelligenceMachine learning algorithmsLanguage modelLearning algorithmsVascular surgery patientsRelevant answersLanguage processingAI chatbotsIntroduction of artificial intelligenceStandalone solutionMedical classification systemsTest scenariosSurgery patientsMedical informationClinical scenariosComplex problemsIntelligenceScientific fieldsComplex clinical scenariosScenariosStatistically significant differenceClinically relevant answersPerformance variationArtificial Intelligence in Cardiovascular Clinical Trials
Cunningham J, Abraham W, Bhatt A, Dunn J, Felker G, Jain S, Lindsell C, Mace M, Martyn T, Shah R, Tison G, Fakhouri T, Psotka M, Krumholz H, Fiuzat M, O’Connor C, Solomon S, Collaboratory H. Artificial Intelligence in Cardiovascular Clinical Trials. Journal Of The American College Of Cardiology 2024, 84: 2051-2062. PMID: 39505413, PMCID: PMC12178241, DOI: 10.1016/j.jacc.2024.08.069.Peer-Reviewed Original ResearchConceptsArtificial intelligenceIntegrate AIPatient privacyClinical trialsRandomized clinical trialsClinical event outcomesCardiovascular clinical trialsIntelligenceInaccurate resultsRandomized trialsInterpreting imagesCardiovascular therapyMedical decision makingDecision makingGold standardValidity of trial resultsClinical trial operationsPrivacyBrain networks and intelligence: A graph neural network based approach to resting state fMRI data
Thapaliya B, Akbas E, Chen J, Sapkota R, Ray B, Suresh P, Calhoun V, Liu J. Brain networks and intelligence: A graph neural network based approach to resting state fMRI data. Medical Image Analysis 2024, 101: 103433. PMID: 37986729, PMCID: PMC10659448, DOI: 10.1016/j.media.2024.103433.Peer-Reviewed Original ResearchGraph neural networksNeural networkGraph isomorphism networkGraph convolutional layersGraph convolutional networkMachine learning modelsMean square errorNetwork connectivity matrixCognitive processesConvolutional layersConvolutional networkPrediction taskModel architectureGraph architectureAdolescent Brain Cognitive Development datasetResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingLearning modelsMiddle frontal gyrusPredicting individual differencesResting state fMRI dataPredictive intelligenceIntelligenceNetworkFunctional network connectivity matricesIntegrated Gradients Demystified: An MRI Case Study on Aβ-T Protein Localization
Dolci G, Morasso C, Cruciani F, Brusini L, Pini L, Calhoun V, Galazzo I, Menegaz G. Integrated Gradients Demystified: An MRI Case Study on Aβ-T Protein Localization. 2024, 00: 1177-1182. DOI: 10.1109/metroxraine62247.2024.10796298.Peer-Reviewed Original ResearchChatGPT Virtual Assistant for Breast Reconstruction: Assessing Preferences for a Traditional Chatbot versus a Human AI VideoBot
Kim T, Yu C, Hinson C, Fung E, Allam O, Nazerali R, Ayyala H. ChatGPT Virtual Assistant for Breast Reconstruction: Assessing Preferences for a Traditional Chatbot versus a Human AI VideoBot. Plastic & Reconstructive Surgery Global Open 2024, 12: e6202. PMID: 39359701, PMCID: PMC11444614, DOI: 10.1097/gox.0000000000006202.Peer-Reviewed Original ResearchText-based chatbotArtificial intelligenceGenerative Pretrained TransformerPretrained TransformerVirtual assistantsAI chatbotsChatGPTChatbotAmazon Mechanical TurkOnline trustVideo platformsInteraction experimentsMechanical TurkMedical applicationsBreast reconstructionZapierReconstructive surgeryUsabilityTrustIntelligence
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