2024
Artificial Intelligence-Assisted Colonoscopy for Polyp Detection : A Systematic Review and Meta-analysis.
Soleymanjahi S, Huebner J, Elmansy L, Rajashekar N, Lüdtke N, Paracha R, Thompson R, Grimshaw A, Foroutan F, Sultan S, Shung D. Artificial Intelligence-Assisted Colonoscopy for Polyp Detection : A Systematic Review and Meta-analysis. Annals Of Internal Medicine 2024 PMID: 39531400, DOI: 10.7326/annals-24-00981.Peer-Reviewed Original ResearchS412 Perceived Advantages and Disadvantages of Adopting Real Time Artificial Intelligence in Colonoscopy by Providers: A Systematic Review
Soleymanjahi S, Kolb J, Foroutan F, Sultan S, Shung D. S412 Perceived Advantages and Disadvantages of Adopting Real Time Artificial Intelligence in Colonoscopy by Providers: A Systematic Review. The American Journal Of Gastroenterology 2024, 119: s292-s293. DOI: 10.14309/01.ajg.0001031016.12767.1d.Peer-Reviewed Original ResearchDetection of Gastrointestinal Bleeding with Large Language Models to Aid Quality Improvement and Appropriate Reimbursement
Zheng N, Keloth V, You K, Kats D, Li D, Deshpande O, Sachar H, Xu H, Laine L, Shung D. Detection of Gastrointestinal Bleeding with Large Language Models to Aid Quality Improvement and Appropriate Reimbursement. Gastroenterology 2024 PMID: 39304088, DOI: 10.1053/j.gastro.2024.09.014.Peer-Reviewed Original ResearchElectronic health recordsOvert gastrointestinal bleedingGastrointestinal bleedingRecurrent bleedingMachine learning modelsHealth recordsClinically relevant applicationsNursing notesLanguage modelAcute gastrointestinal bleedingQuality improvementLearning modelsDetection of gastrointestinal bleedingReimbursementIdentification of clinical conditionsSeparate hospitalsQuality measuresHospitalBleedingClinical conditionsPatient managementEarly identificationPatientsReimbursement codesCoding algorithmEditorial: Incidence and predictors of major gastrointestinal bleeding in patients on aspirin, low‐dose rivaroxaban or the combination: Secondary analysis of the COMPASS randomised controlled trial
Sehgal K, Shung D. Editorial: Incidence and predictors of major gastrointestinal bleeding in patients on aspirin, low‐dose rivaroxaban or the combination: Secondary analysis of the COMPASS randomised controlled trial. Alimentary Pharmacology & Therapeutics 2024, 60: 961-962. PMID: 39219413, DOI: 10.1111/apt.18195.Commentaries, Editorials and LettersOn the Wasserstein Median of Probability Measures
You K, Shung D, Giuffrè M. On the Wasserstein Median of Probability Measures. Journal Of Computational And Graphical Statistics 2024, ahead-of-print: 1-14. DOI: 10.1080/10618600.2024.2374580.Peer-Reviewed Original ResearchHow 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 sourcesMetabolomicsEndoscopyTherapyValidation of an Electronic Health Record–Based Machine Learning Model Compared With Clinical Risk Scores for Gastrointestinal Bleeding
Shung D, Chan C, You K, Nakamura S, Saarinen T, Zheng N, Simonov M, Li D, Tsay C, Kawamura Y, Shen M, Hsiao A, Sekhon J, Laine L. Validation of an Electronic Health Record–Based Machine Learning Model Compared With Clinical Risk Scores for Gastrointestinal Bleeding. Gastroenterology 2024, 167: 1198-1212. PMID: 38971198, PMCID: PMC11493512, DOI: 10.1053/j.gastro.2024.06.030.Peer-Reviewed Original ResearchElectronic health recordsGlasgow-Blatchford scoreEmergency departmentVery-low-risk patientsRisk scoreOakland scoreMachine learning modelsStructured data fieldsClinical risk scoreGastrointestinal bleedingAll-cause mortalityHealth recordsLearning modelsManual data entrySecondary analysisRisk stratification scoresAssess proportionRed blood-cell transfusionPrimary outcomeProportion of patientsData entryOvert gastrointestinal bleedingPrimary analysisReceiver-operating-characteristic curveVery-low-riskLetter: Shifting focus—From ChatGPT to specialised medical LLMs: Authors' reply
Giuffrè M, Kresevic S, You K, Dupont J, Huebner J, Grimshaw A, Shung D. Letter: Shifting focus—From ChatGPT to specialised medical LLMs: Authors' reply. Alimentary Pharmacology & Therapeutics 2024, 60: 417-418. PMID: 38884531, DOI: 10.1111/apt.18125.Commentaries, Editorials and LettersSAT-338-YI Using retrieval augmented generation to increase large language models accuracy: a proof-of-concept pipeline on european hepatitis C virus (HCV) guidelines
Giuffrè M, Kresevic S, Croce’ S, Shung D. SAT-338-YI Using retrieval augmented generation to increase large language models accuracy: a proof-of-concept pipeline on european hepatitis C virus (HCV) guidelines. Journal Of Hepatology 2024, 80: s731. DOI: 10.1016/s0168-8278(24)02060-9.Peer-Reviewed Original ResearchOptimizing large language models in digestive disease: strategies and challenges to improve clinical outcomes
Giuffrè M, Kresevic S, Pugliese N, You K, Shung D. Optimizing large language models in digestive disease: strategies and challenges to improve clinical outcomes. Liver International 2024, 44: 2114-2124. PMID: 38819632, DOI: 10.1111/liv.15974.Peer-Reviewed Original ResearchSupervised fine-tuningHuman feedbackLanguage modelAccurate information retrievalInformation retrievalReinforcement learningDomain knowledgeText corpusNeural networkModel trainingAdaptive methodField of digestive diseasesFine-tuningWindow limitRetrievalIncreased accuracyAccuracyDigestive diseasesImprove healthcareDefinition of accuracyLearningIncrease patients' qualityClinical decision-makingSpecialized knowledgeDiverse sourcesSystematic review: The use of large language models as medical chatbots in digestive diseases
Giuffrè M, Kresevic S, You K, Dupont J, Huebner J, Grimshaw A, Shung D. Systematic review: The use of large language models as medical chatbots in digestive diseases. Alimentary Pharmacology & Therapeutics 2024, 60: 144-166. PMID: 38798194, DOI: 10.1111/apt.18058.Peer-Reviewed Original ResearchLanguage modelAdverse patient safety eventsPatient safety eventsClinical decision supportRisk of biasSystematic literature searchWeb of Science Core CollectionCombination of keywordsMedical chatbotTriage recommendationsHealthcare systemScience Core CollectionNecessary careSafety eventsOverburden healthcare systemsMedical adviceOvid MEDLINEMultiple specialtiesDecision supportOvid EmbaseCochrane LibrarySingle-study resultsGoogle ScholarLiterature searchGastroenterologyHuman-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 intuitionTrustTu2034 PERFORMANCE OF DIFFERENT COMPUTER-AIDED DETECTION (CADE) PLATFORMS COMPARED TO CONVENTIONAL COLONOSCOPY: A SYSTEMATIC REVIEW AND META-ANALYSIS
Soleymanjahi S, Huebner J, Elmansy L, Rajashekar N, Paracha R, Shung D. Tu2034 PERFORMANCE OF DIFFERENT COMPUTER-AIDED DETECTION (CADE) PLATFORMS COMPARED TO CONVENTIONAL COLONOSCOPY: A SYSTEMATIC REVIEW AND META-ANALYSIS. Gastroenterology 2024, 166: s-1501. DOI: 10.1016/s0016-5085(24)03891-5.Peer-Reviewed Original ResearchMo1066 LARGE LANGUAGE MODEL-BASED SIMULATED PATIENTS WITH UPPER GASTROINTESTINAL BLEEDING FOR MEDICAL EDUCATION – A PILOT STUDY WITH EMPATHGPT
Rajashekar N, Chan C, Laine L, Shung D. Mo1066 LARGE LANGUAGE MODEL-BASED SIMULATED PATIENTS WITH UPPER GASTROINTESTINAL BLEEDING FOR MEDICAL EDUCATION – A PILOT STUDY WITH EMPATHGPT. Gastroenterology 2024, 166: s-933. DOI: 10.1016/s0016-5085(24)02628-3.Peer-Reviewed Original ResearchSu1979 GUTGPT: NOVEL LARGE LANGUAGE MODEL PIPELINE OUTPERFORMS OTHER LARGE LANGUAGE MODELS IN ACCURACY AND SIMILARITY TO INTERNATIONAL EXPERTS FOR GUIDELINE RECOMMENDED MANAGEMENT OF PATIENTS WITH UPPER GASTROINTESTINAL BLEEDING
Giuffrè M, You K, Chung S, Kresevic S, Chan C, Saarinen T, Nakamura S, Laine L, Sung J, Garcia-Tsao G, Gralnek I, Barkun A, Sekhon J, Shung D. Su1979 GUTGPT: NOVEL LARGE LANGUAGE MODEL PIPELINE OUTPERFORMS OTHER LARGE LANGUAGE MODELS IN ACCURACY AND SIMILARITY TO INTERNATIONAL EXPERTS FOR GUIDELINE RECOMMENDED MANAGEMENT OF PATIENTS WITH UPPER GASTROINTESTINAL BLEEDING. Gastroenterology 2024, 166: s-889-s-890. DOI: 10.1016/s0016-5085(24)02528-9.Peer-Reviewed Original ResearchTu2010 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 ResearchThe Reply
Li D, Shung D. The Reply. The American Journal Of Medicine 2024, 137: e99. PMID: 38679450, DOI: 10.1016/j.amjmed.2024.01.017.Commentaries, Editorials and Letters407 IMPACT OF ARTIFICIAL INTELLIGENCE SYSTEMS FOR UPPER GASTROINTESTINAL BLEEDING ON CLINICIAN TRUST AND LEARNING USING LARGE LANGUAGE MODELS: A RANDOMIZED PILOT SIMULATION STUDY
Chung S, Rajashekar N, Pu Y, Shin Y, Giuffrè M, Chan C, You K, Saarinen T, Hsiao A, Sekhon J, Wong A, Evans L, McCall T, Kizilcec R, Laine L, Shung D. 407 IMPACT OF ARTIFICIAL INTELLIGENCE SYSTEMS FOR UPPER GASTROINTESTINAL BLEEDING ON CLINICIAN TRUST AND LEARNING USING LARGE LANGUAGE MODELS: A RANDOMIZED PILOT SIMULATION STUDY. Gastroenterology 2024, 166: s-95-s-96. DOI: 10.1016/s0016-5085(24)00715-7.Peer-Reviewed Original ResearchTu1649 SIMULATING THE PATIENT-PRACTITIONER RELATIONSHIP IN PATIENTS WITH IRRITABLE BOWEL SYNDROME WITH LARGE LANGUAGE MODELBASED TOOLS – A PROOF OF CONCEPT
Rajashekar N, Chan C, Deutsch J, Laine L, Shung D. Tu1649 SIMULATING THE PATIENT-PRACTITIONER RELATIONSHIP IN PATIENTS WITH IRRITABLE BOWEL SYNDROME WITH LARGE LANGUAGE MODELBASED TOOLS – A PROOF OF CONCEPT. Gastroenterology 2024, 166: s-1364. DOI: 10.1016/s0016-5085(24)03586-8.Peer-Reviewed Original ResearchTu2029 DOES COMPUTER-AIDED DETECTION (CADE) OFFER ANY ADVANTAGE TO CONVENTIONAL COLONOSCOPY: A COMPREHENSIVE COMPARISON OF EFFICACY AND SAFETY MEASURES?
Soleymanjahi S, Huebner J, Elmansy L, Rajashekar N, Paracha R, Shung D. Tu2029 DOES COMPUTER-AIDED DETECTION (CADE) OFFER ANY ADVANTAGE TO CONVENTIONAL COLONOSCOPY: A COMPREHENSIVE COMPARISON OF EFFICACY AND SAFETY MEASURES? Gastroenterology 2024, 166: s-1499. DOI: 10.1016/s0016-5085(24)03886-1.Peer-Reviewed Original Research