2024
How Artificial Intelligence Will Transform Clinical Care, Research, and Trials for Inflammatory Bowel Disease
Silverman A, Shung D, Stidham R, Kochhar G, Iacucci M. How Artificial Intelligence Will Transform Clinical Care, Research, and Trials for Inflammatory Bowel Disease. Clinical Gastroenterology And Hepatology 2024 PMID: 38992406, DOI: 10.1016/j.cgh.2024.05.048.Peer-Reviewed Original ResearchInflammatory bowel diseaseBowel diseasePredicting response to therapyArtificial intelligenceResponse to therapyDisease Activity ScoreMulti-modal data sourcesDirections of AIBowel damageAI applicationsDiseaseClinical careTransform clinical careComputer-based methodologyDrug discoveryComplex diseasesCritical challengesData sourcesMetabolomicsEndoscopyTherapyHuman-Algorithmic Interaction Using a Large Language Model-Augmented Artificial Intelligence Clinical Decision Support System
Rajashekar N, Shin Y, Pu Y, Chung S, You K, Giuffre M, Chan C, Saarinen T, Hsiao A, Sekhon J, Wong A, Evans L, Kizilcec R, Laine L, Mccall T, Shung D. Human-Algorithmic Interaction Using a Large Language Model-Augmented Artificial Intelligence Clinical Decision Support System. 2024, 1-20. DOI: 10.1145/3613904.3642024.Peer-Reviewed Original ResearchClinical decision support systemsHuman-computer interactionDecision support systemArtificial intelligenceAI-CDSSIntelligent clinical decision support systemSupport systemIntegration of artificial intelligenceHuman-algorithm interactionsEase-of-useLanguage modelHuman algorithmAI systemsSocio-technological challengesHealth-care providersMedical student participationQualitative themesClinical simulationClinical expertiseUpper gastrointestinal bleedingUsabilityBorderline decisionsLanguageClinical intuitionTrustTu2010 PROVIDER TRUST TOWARDS ADOPTING REAL TIME ARTIFICIAL INTELLIGENCE IN COLONOSCOPY: A SYSTEMATIC REVIEW
Soleymanjahi S, Kolb J, Chung S, Foroutan F, Sultan S, Shung D. Tu2010 PROVIDER TRUST TOWARDS ADOPTING REAL TIME ARTIFICIAL INTELLIGENCE IN COLONOSCOPY: A SYSTEMATIC REVIEW. Gastroenterology 2024, 166: s-1490-s-1491. DOI: 10.1016/s0016-5085(24)03867-8.Peer-Reviewed Original ResearchArtificial intelligenceSystematic reviewChapter 10 Human-machine interaction: AI-assisted medicine, instead of AI-driven medicine
Kizilcec R, Shung D, Sung J. Chapter 10 Human-machine interaction: AI-assisted medicine, instead of AI-driven medicine. 2024, 131-140. DOI: 10.1016/b978-0-323-95068-8.00010-8.Peer-Reviewed Original ResearchAI systemsArtificial intelligenceExplainable AI techniquesDesigning AI systemsDevelopment of AI systemsIntegration of AIClinical workflowAI techniquesSociotechnical challengesAlgorithm aversionEffective useSystem outputWorkflowInteraction perspectiveSystemHeuristicsIntelligenceArtificialImprove patient careClinical care decisionsCare decisions
2021
Challenges of developing artificial intelligence‐assisted tools for clinical medicine
Shung DL, Sung JJY. Challenges of developing artificial intelligence‐assisted tools for clinical medicine. Journal Of Gastroenterology And Hepatology 2021, 36: 295-298. PMID: 33624889, DOI: 10.1111/jgh.15378.Peer-Reviewed Original ResearchConceptsArtificial intelligenceAI toolsClinical decision supportMachine learningData managementMassive amountsDecision supportVibrant ecosystemClinical careComputational toolsRight timeMultiple sourcesQuality of careOperational levelRisk stratificationManometric testingRadiologic imagingClinical managementRight patientRight amountClinical practiceToolCare deliveryVisual findingsAreas of medicineAdvancing care for acute gastrointestinal bleeding using artificial intelligence
Shung DL. Advancing care for acute gastrointestinal bleeding using artificial intelligence. Journal Of Gastroenterology And Hepatology 2021, 36: 273-278. PMID: 33624892, DOI: 10.1111/jgh.15372.Peer-Reviewed Original ResearchConceptsElectronic health recordsAcute gastrointestinal bleedingIntegration of machineHealth recordsNeural network modelGastrointestinal bleedingRisk prediction toolsNeural network-based analysisArtificial intelligenceMachine learningDecision supportRisk patientsNetwork modelReal timeMachineAlgorithmPrediction toolsClinical risk scoreLower gastrointestinal bleedingLow-risk patientsHigh-risk patientsProspective clinical trialsTriage of patientsClinician risk assessmentDelivery of care
2020
How Artificial Intelligence Will Impact Colonoscopy and Colorectal Screening
Shung DL, Byrne MF. How Artificial Intelligence Will Impact Colonoscopy and Colorectal Screening. Gastrointestinal Endoscopy Clinics Of North America 2020, 30: 585-595. PMID: 32439090, DOI: 10.1016/j.giec.2020.02.010.Peer-Reviewed Original ResearchConceptsArtificial intelligenceArtificial intelligence-based technologiesDeep learning algorithmsComputer-assisted diagnosisComputer-assisted detectionLearning algorithmCenter efficiencyIntelligenceUnnecessary costsKey challengesColorectal screeningWorkflowDetection rateLow-risk polypsAdenoma detection rateTechnologyQuality of screeningTreatment of cancerInterpretabilityGastrointestinal tractAlgorithmClinical integrationCostPolypsDiagnosis