Detection 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 algorithmOptimizing 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 intuitionTrustSu1979 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 ResearchLanguage model407 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 Research543 IDENTIFYING OVERT SIGNS OF ACUTE GASTROINTESTINAL BLEEDING IN THE ELECTRONIC HEALTH RECORD WITH LARGE LANGUAGE MODELS
Zheng N, Keloth V, You K, Li D, Xu H, Laine L, Shung D. 543 IDENTIFYING OVERT SIGNS OF ACUTE GASTROINTESTINAL BLEEDING IN THE ELECTRONIC HEALTH RECORD WITH LARGE LANGUAGE MODELS. Gastroenterology 2024, 166: s-124-s-125. DOI: 10.1016/s0016-5085(24)00776-5.Peer-Reviewed Original ResearchLanguage model1244 AUTOMATED IDENTIFICATION OF RECURRENT GASTROINTESTINAL BLEEDING USING ELECTRONIC HEALTH RECORDS AND LARGE LANGUAGE MODELS
Zheng N, Keloth V, You K, Li D, Xu H, Laine L, Shung D. 1244 AUTOMATED IDENTIFICATION OF RECURRENT GASTROINTESTINAL BLEEDING USING ELECTRONIC HEALTH RECORDS AND LARGE LANGUAGE MODELS. Gastroenterology 2024, 166: s-292. DOI: 10.1016/s0016-5085(24)01152-1.Peer-Reviewed Original Research1059 ENHANCING CLINICAL DECISION SUPPORT WITH LARGE LANGUAGE MODELS: A TAILORED PIPELINE FOR ACCURATE INTERPRETATION OF HEPATITIS C MANAGEMENT GUIDELINES
Kresevic S, Giuffrè M, Shung D. 1059 ENHANCING CLINICAL DECISION SUPPORT WITH LARGE LANGUAGE MODELS: A TAILORED PIPELINE FOR ACCURATE INTERPRETATION OF HEPATITIS C MANAGEMENT GUIDELINES. Gastroenterology 2024, 166: s-1564. DOI: 10.1016/s0016-5085(24)04052-6.Peer-Reviewed Original ResearchLanguage modelOptimization of hepatological clinical guidelines interpretation by large language models: a retrieval augmented generation-based framework
Kresevic S, Giuffrè M, Ajcevic M, Accardo A, Crocè L, Shung D. Optimization of hepatological clinical guidelines interpretation by large language models: a retrieval augmented generation-based framework. Npj Digital Medicine 2024, 7: 102. PMID: 38654102, PMCID: PMC11039454, DOI: 10.1038/s41746-024-01091-y.Peer-Reviewed Original ResearchClinical decision support systemsFew-shot learningLanguage modelImprove clinical decision support systemsDecision support systemText similarity scoresText similarityAblation studiesImprove overall accuracyGeneration accuracyRight informationAccurate outputSupport systemTransform healthcareIncreasing levels of complexityHospital workflowOverall accuracyRight providerTurbo modelLearning strategiesLevel of complexityLearningRetrievalCorpus of textsAccuracy