Dennis Shung
MD, MHS, PhD
Assistant Professor of Medicine (Digestive Diseases); Director of Digital Health, Digestive Diseases
Research & Publications
Biography
News
Research Summary
I am interested in the application of machine learning - from algorithmic development, validation, and implementation to human-algorithmic interaction - in enhancing clinical decision-making in gastrointestinal diseases.
Extensive Research Description
Dennis Shung, MD, MHS, PhD is Assistant Professor of Medicine and Director of Digital Health in the section of Digestive Diseases, Department of Medicine at Yale. He is a physician data scientist and gastroenterologist working in the intersection of translational informatics, algorithmic development, and implementation science with a special focus on the management of acute gastrointestinal bleeding. He did his undergraduate studies at Rice University, received his MD from Baylor College of Medicine, MHS in Clinical Informatics from Yale, and PhD from Yale. He founded the Human+Artificial Intelligence in Medicine (HAIM) lab at Yale, which is funded by the National Institutes of Health, the American Gastroenterological Association, and the Yale Center for Clinical Investigation. He was awarded a Career Development Award from the National Institutes of Health, the 2022 AGA–Medtronic Pilot Research Award in Artificial Intelligence; the Research Scholar Award from the American Gastroenterological Association; the Iva Dostanic, MD, PhD, Physician-Scientist Trainee Award; and the Samuel Kushlan Award for Excellence in Research.
Coauthors
Research Interests
Health Services Accessibility
Selected Publications
- Sex, Race, and Ethnicity Differences in Patients Presenting With Diverticular Disease at Emergency Departments in the United States: A National Cross-Sectional StudyZheng N, Ma W, Shung D, Strate L, Chan A. Sex, Race, and Ethnicity Differences in Patients Presenting With Diverticular Disease at Emergency Departments in the United States: A National Cross-Sectional Study. Gastro Hep Advances 2024, 3: 178-180. DOI: 10.1016/j.gastha.2023.11.012.
- Achieving Value by Risk Stratification With Machine Learning Model or Clinical Risk Score in Acute Upper Gastrointestinal Bleeding: A Cost Minimization AnalysisShung D, Lin J, Laine L. Achieving Value by Risk Stratification With Machine Learning Model or Clinical Risk Score in Acute Upper Gastrointestinal Bleeding: A Cost Minimization Analysis. The American Journal Of Gastroenterology 2023, 119: 371-373. PMID: 37753930, PMCID: PMC10872988, DOI: 10.14309/ajg.0000000000002520.
- Harnessing the power of synthetic data in healthcare: innovation, application, and privacyGiuffrè M, Shung D. Harnessing the power of synthetic data in healthcare: innovation, application, and privacy. Npj Digital Medicine 2023, 6: 186. PMID: 37813960, PMCID: PMC10562365, DOI: 10.1038/s41746-023-00927-3.
- Trends in Upper Gastrointestinal Bleeding in Patients on Primary Prevention Aspirin: A Nationwide Emergency Department Sample Analysis, 2016-2020Li D, Laine L, Shung D. Trends in Upper Gastrointestinal Bleeding in Patients on Primary Prevention Aspirin: A Nationwide Emergency Department Sample Analysis, 2016-2020. The American Journal Of Medicine 2023, 136: 1179-1186.e1. PMID: 37696350, PMCID: PMC10841721, DOI: 10.1016/j.amjmed.2023.08.010.
- From Tool to Team Member: A Second Set of Eyes for Polyp Detection.Shung D. From Tool to Team Member: A Second Set of Eyes for Polyp Detection. Annals Of Internal Medicine 2023, 176: 1271-1272. PMID: 37639722, DOI: 10.7326/m23-2022.
- On the Spherical Laplace DistributionYou K, Shung D. On the Spherical Laplace Distribution. 2023, 00: 1-8. DOI: 10.23919/fusion52260.2023.10224108.
- Rdimtools: An R package for dimension reduction and intrinsic dimension estimationYou K, Shung D. Rdimtools: An R package for dimension reduction and intrinsic dimension estimation. Software Impacts 2022, 14: 100414. DOI: 10.1016/j.simpa.2022.100414.
- IMPACT OF LONG-TERM ANTITHROMBOTIC THERAPY ON PATIENTS WHO PRESENT WITH UPPER GASTROINTESTINAL BLEEDINGZheng N, Canavan M, Laine L, Shung D. IMPACT OF LONG-TERM ANTITHROMBOTIC THERAPY ON PATIENTS WHO PRESENT WITH UPPER GASTROINTESTINAL BLEEDING. Gastrointestinal Endoscopy 2022, 95: ab439-ab440. DOI: 10.1016/j.gie.2022.04.1122.
- Su1001: ARTIFICIAL INTELLIGENCE ASSISTED DIAGNOSIS HAS MORE EVIDENCE TO IMPROVE GI OUTCOME THAN OTHER SPECIALTIES: AN ANALYSIS OF RCT FROM 2009-2021.Lam T, Cheung F, Munro Y, Lim K, Shung D, Sung J. Su1001: ARTIFICIAL INTELLIGENCE ASSISTED DIAGNOSIS HAS MORE EVIDENCE TO IMPROVE GI OUTCOME THAN OTHER SPECIALTIES: AN ANALYSIS OF RCT FROM 2009-2021. Gastroenterology 2022, 162: s-473-s-474. DOI: 10.1016/s0016-5085(22)61128-4.
- 271: EXTERNAL VALIDATION OF AN ELECTRONIC HEALTH RECORD-BASED DEEP LEARNING MODEL FOR AUTOMATED RAPID RISK STRATIFICATION OF PATIENTS PRESENTING WITH ACUTE GASTROINTESTINAL BLEEDINGShung D, Simonov M, Tsay C, Kawamura Y, Partridge C, Thomas P, Zheng N, Tay K, Hsiao A, Laine L. 271: EXTERNAL VALIDATION OF AN ELECTRONIC HEALTH RECORD-BASED DEEP LEARNING MODEL FOR AUTOMATED RAPID RISK STRATIFICATION OF PATIENTS PRESENTING WITH ACUTE GASTROINTESTINAL BLEEDING. Gastroenterology 2022, 162: s-61. DOI: 10.1016/s0016-5085(22)60151-3.
- Mo1056: COST MINIMIZATION ANALYSIS OF APPLYING RISK STRATIFICATION TO PATIENTS PRESENTING WITH ACUTE UPPER GASTROINTESTINAL BLEEDINGShung D, Lin J, Laine L. Mo1056: COST MINIMIZATION ANALYSIS OF APPLYING RISK STRATIFICATION TO PATIENTS PRESENTING WITH ACUTE UPPER GASTROINTESTINAL BLEEDING. Gastroenterology 2022, 162: s-678. DOI: 10.1016/s0016-5085(22)61589-0.
- 270: TRENDS IN CHARACTERISTICS, MANAGEMENT, AND OUTCOMES OF PATIENTS PRESENTING WITH GASTROINTESTINAL BLEEDING TO EMERGENCY DEPARTMENTS IN THE UNITED STATES FROM 2006 TO 2019Zheng N, Tsay C, Shung D, Laine L. 270: TRENDS IN CHARACTERISTICS, MANAGEMENT, AND OUTCOMES OF PATIENTS PRESENTING WITH GASTROINTESTINAL BLEEDING TO EMERGENCY DEPARTMENTS IN THE UNITED STATES FROM 2006 TO 2019. Gastroenterology 2022, 162: s-60-s-61. DOI: 10.1016/s0016-5085(22)60150-1.
- 1150: DISPARITIES IN ACCESS TO ENDOSCOPIC EVALUATION FOR PATIENTS WITH ACUTE UPPER GASTROINTESTINAL BLEEDING PRESENTING TO THE EMERGENCY DEPARTMENTRodriguez N, Zheng N, Mezzacappa C, Canavan M, Laine L, Shung D. 1150: DISPARITIES IN ACCESS TO ENDOSCOPIC EVALUATION FOR PATIENTS WITH ACUTE UPPER GASTROINTESTINAL BLEEDING PRESENTING TO THE EMERGENCY DEPARTMENT. Gastroenterology 2022, 162: s-272-s-273. DOI: 10.1016/s0016-5085(22)60644-9.
- Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover’s DistanceTong A, Huguet G, Shung D, Natik A, Kuchroo M, Lajoie G, Wolf G, Krishnaswamy S. Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover’s Distance. 2013 IEEE International Conference On Acoustics, Speech And Signal Processing 2022, 00: 5647-5651. PMID: 36628172, PMCID: PMC9828741, DOI: 10.1109/icassp43922.2022.9746556.
- MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record DataGerasimiuk M, Shung D, Tong A, Stanley A, Schultz M, Ngu J, Laine L, Wolf G, Krishnaswamy S. MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. 2021, 00: 4694-4704. DOI: 10.1109/bigdata52589.2021.9672045.
- Sa097 CHANGING PRACTICES AND OUTCOMES IN PATIENTS PRESENTING TO THE EMERGENCY DEPARTMENT WITH GASTROINTESTINAL BLEEDINGTsay C, Shung D, Laine L. Sa097 CHANGING PRACTICES AND OUTCOMES IN PATIENTS PRESENTING TO THE EMERGENCY DEPARTMENT WITH GASTROINTESTINAL BLEEDING. Gastroenterology 2021, 160: s-420. DOI: 10.1016/s0016-5085(21)01710-8.
- Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unitShung D, Huang J, Castro E, Tay JK, Simonov M, Laine L, Batra R, Krishnaswamy S. Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit. Scientific Reports 2021, 11: 8827. PMID: 33893364, PMCID: PMC8065139, DOI: 10.1038/s41598-021-88226-3.
- The Clinician's Guide to the Machine Learning GalaxyShen L, Kann BH, Taylor RA, Shung DL. The Clinician's Guide to the Machine Learning Galaxy. Frontiers In Physiology 2021, 12: 658583. PMID: 33889088, PMCID: PMC8056037, DOI: 10.3389/fphys.2021.658583.
- Challenges of developing artificial intelligence‐assisted tools for clinical medicineShung 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.
- Advancing care for acute gastrointestinal bleeding using artificial intelligenceShung 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.
- Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rulesShung D, Tsay C, Laine L, Chang D, Li F, Thomas P, Partridge C, Simonov M, Hsiao A, Tay JK, Taylor A. Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules. Journal Of Gastroenterology And Hepatology 2021, 36: 1590-1597. PMID: 33105045, DOI: 10.1111/jgh.15313.
- S0521 Adopting a GI Hospitalist Model: A New Method for Increasing Procedural VolumeShung D, Hung K, Laine L, Hughes M. S0521 Adopting a GI Hospitalist Model: A New Method for Increasing Procedural Volume. The American Journal Of Gastroenterology 2020, 115: s259-s259. DOI: 10.14309/01.ajg.0000704132.96009.7f.
- Machine Learning Prognostic Models for Gastrointestinal Bleeding Using Electronic Health Record Data.Shung D, Laine L. Machine Learning Prognostic Models for Gastrointestinal Bleeding Using Electronic Health Record Data. The American Journal Of Gastroenterology 2020, 115: 1199-1200. PMID: 32530828, PMCID: PMC7415736, DOI: 10.14309/ajg.0000000000000720.
- 928 AN ELECTRONIC HEALTH RECORD-BASED MACHINE LEARNING MODEL TO PROVIDE AUTOMATED RAPID RISK STRATIFICATION OF PATIENTS PRESENTING WITH GASTROINTESTINAL BLEEDING OUTPERFORMS GLASGOW-BLATCHFORD SCOREShung D, Simonov M, Tsay C, Hsiao A, Partridge C, Thomas P, Laine L. 928 AN ELECTRONIC HEALTH RECORD-BASED MACHINE LEARNING MODEL TO PROVIDE AUTOMATED RAPID RISK STRATIFICATION OF PATIENTS PRESENTING WITH GASTROINTESTINAL BLEEDING OUTPERFORMS GLASGOW-BLATCHFORD SCORE. Gastroenterology 2020, 158: s-184-s-185. DOI: 10.1016/s0016-5085(20)31145-8.
- Sa1035 IDENTIFYING PATIENTS WITH ACUTE GASTROINTESTINAL BLEEDING WITH ELECTRONIC HEALTH RECORD PHENOTYPESShung D, Tsay C, Laine L, Thomas P, Partridge C, Hsiao A, Taylor R. Sa1035 IDENTIFYING PATIENTS WITH ACUTE GASTROINTESTINAL BLEEDING WITH ELECTRONIC HEALTH RECORD PHENOTYPES. Gastroenterology 2020, 158: s-251-s-252. DOI: 10.1016/s0016-5085(20)31310-x.
- How Artificial Intelligence Will Impact Colonoscopy and Colorectal ScreeningShung 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.
- Early Colonoscopy Does Not Improve Outcomes of Patients With Lower Gastrointestinal Bleeding: Systematic Review of Randomized TrialsTsay C, Shung D, Stemmer Frumento K, Laine L. Early Colonoscopy Does Not Improve Outcomes of Patients With Lower Gastrointestinal Bleeding: Systematic Review of Randomized Trials. Clinical Gastroenterology And Hepatology 2019, 18: 1696-1703.e2. PMID: 31843595, PMCID: PMC7292779, DOI: 10.1016/j.cgh.2019.11.061.
- Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal BleedingShung DL, Au B, Taylor RA, Tay JK, Laursen SB, Stanley AJ, Dalton HR, Ngu J, Schultz M, Laine L. Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding. Gastroenterology 2019, 158: 160-167. PMID: 31562847, PMCID: PMC7004228, DOI: 10.1053/j.gastro.2019.09.009.
- Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: A Systematic ReviewShung D, Simonov M, Gentry M, Au B, Laine L. Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: A Systematic Review. Digestive Diseases And Sciences 2019, 64: 2078-2087. PMID: 31055722, DOI: 10.1007/s10620-019-05645-z.
- 325 – Development and Validation of Machine Learning Models to Predict Outcomes in Ugib with Comparison to Clinical Risk ScoresShung D, Au B, Taylor R, Tay K, Laursen S, Stanley A, Dalton H, Ngu J, Schultz M, Laine L. 325 – Development and Validation of Machine Learning Models to Predict Outcomes in Ugib with Comparison to Clinical Risk Scores. Gastroenterology 2019, 156: s-64. DOI: 10.1016/s0016-5085(19)36945-8.
- Liver Disease: A Clinical CasebookISBN 978-3-319-98505-3
- Drug-Induced Liver InjuryShung D, Lim J. Drug-Induced Liver Injury. 2018, 1-10. DOI: 10.1007/978-3-319-98506-0_1.
- Mo1180 - Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: Systematic Review and Meta-AnalysisShung D, Simonov M, Au B, Laine L. Mo1180 - Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: Systematic Review and Meta-Analysis. Gastroenterology 2018, 154: s-697-s-698. DOI: 10.1016/s0016-5085(18)32461-2.
- Liver Capsule: Portal Hypertension and Varices: Pathogenesis, Stages, and ManagementShung DL, Garcia‐Tsao G. Liver Capsule: Portal Hypertension and Varices: Pathogenesis, Stages, and Management. Hepatology 2017, 65: 1038-1038. PMID: 28032650, DOI: 10.1002/hep.29026.
- 42 Impact of a Novel Volunteer-Run Discharge Planning Program on Follow-Up Appointment AdherenceShung D, Lin J, Chou A, Heberlig S, Medford-Davis L, Siler-Fisher A. 42 Impact of a Novel Volunteer-Run Discharge Planning Program on Follow-Up Appointment Adherence. Annals Of Emergency Medicine 2015, 66: s14. DOI: 10.1016/j.annemergmed.2015.07.071.
- Unlocking Secrets of Inflammatory Bowel DiseaseShung DL and Allen JI. Science & Diplomacy, Vol. 4, No. 4 December 2015 http://www.sciencediplomacy.org/perspective/2015/unlocking-secrets-of-inflammatory-bowel- disease
- Medical and Surgical Complications of Inflammatory Bowel Disease in the Elderly: A Systematic ReviewShung DL, Abraham B, Sellin J, Hou JK. Medical and Surgical Complications of Inflammatory Bowel Disease in the Elderly: A Systematic Review. Digestive Diseases And Sciences 2014, 60: 1132-1140. PMID: 25501923, DOI: 10.1007/s10620-014-3462-2.