David Chartash, PhD
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Yale School of Medicine
100 College Street
New Haven, CT 06511
United States
About
Titles
Lecturer in Biomedical Informatics and Data Science
Biography
Dr. Chartash's interests are in understanding the adage in medicine that,
The history is the foundation of diagnosis, management and rapport with the patient, and that diagnosis is based on, first, a focused and meticulous history, followed by a focused and confirmatory physical examination and ending with a parsimonious ancillary investigation. — Crombie, D. L. "General Practice Today and Tomorrow. X. Diagnostic Methods." The Practitioner 191 (1963): 539-545.
Methodologically, his research aims to model information within the medical record and clinical encounter through the use of cognitive science, computational linguistic and complex systems science approaches.
Dr. Chartash earned his bachelor's degree in engineering science from The University of Western Ontario in electrical engineering, focusing on biomedical signals and systems analysis. He completed a masters degree in health science by research at the University of Toronto in clinical engineering, during the course of this degree, practicing as an engineer at the Toronto Health Economics and Technology Assessment Collaborative and Toronto General Hospital. He holds a doctorate in philosophy from Indiana University Bloomington, specializing in medical informatics and complex systems. During the course of this doctorate he was a fellow at the Center for Biomedical Informatics at the Regenstrief Institute, as well as the Department of Pediatrics at the Indiana University School of Medicine.
Education & Training
- PhD
- Indiana University Bloomington, Medical Informatics and Complex Systems
- MHS
- University of Toronto, Clinical Engineering
- BEngSci
- The University of Western Ontario, Electrical Engineering
Research
Overview
Medical Subject Headings (MeSH)
Biomedical Engineering; Clinical Decision-Making; Decision Making; Decision Support Systems, Clinical; Decision Theory; Diagnosis, Computer-Assisted; Diagnosis, Differential; Diagnostic Errors; Folklore; General Practice; History of Medicine; Information Theory; Medical Informatics; Medical Writing; Narrative Medicine; Pediatrics; Semantics; Systems Integration
Research at a Glance
Yale Co-Authors
Frequent collaborators of David Chartash's published research.
Publications Timeline
A big-picture view of David Chartash's research output by year.
Research Interests
Research topics David Chartash is interested in exploring.
Andrew Taylor, MD, MHS
Vimig Socrates, MS
Gail D'Onofrio, MD, MS
Hyung Paek, MD, MSEE
Rohit Sangal, MD, MBA, FACEP
Andreas Coppi
26Publications
1,079Citations
Medical Informatics
Publications
2024
Computationally derived transition points across phases of clinical care
Gilson A, Chartash D, Taylor R, Hart L. Computationally derived transition points across phases of clinical care. Npj Digital Medicine 2024, 7: 151. PMID: 38862589, PMCID: PMC11167560, DOI: 10.1038/s41746-024-01145-1.Peer-Reviewed Original ResearchAltmetricPatient-Representing Population Perceptions of GPT-Generated vs. Standard Emergency Department Discharge Instructions: Randomized Blind Survey Assessment (Preprint)
Huang T, Safranek C, Socrates V, Chartash D, Wright D, Dilip M, Sangal R, Taylor R. Patient-Representing Population Perceptions of GPT-Generated vs. Standard Emergency Department Discharge Instructions: Randomized Blind Survey Assessment (Preprint). Journal Of Medical Internet Research 2024 DOI: 10.2196/60336.Peer-Reviewed Original ResearchAutomated HEART score determination via ChatGPT: Honing a framework for iterative prompt development
Safranek C, Huang T, Wright D, Wright C, Socrates V, Sangal R, Iscoe M, Chartash D, Taylor R. Automated HEART score determination via ChatGPT: Honing a framework for iterative prompt development. Journal Of The American College Of Emergency Physicians Open 2024, 5: e13133. PMID: 38481520, PMCID: PMC10936537, DOI: 10.1002/emp2.13133.Peer-Reviewed Original ResearchCitationsConceptsPrompt designsChest pain evaluationRule-based logicScore determinationLanguage modelPrivacy safeguardsPrompt improvementExtract insightsPain evaluationClinical notesRate of responseDiagnostic performancePhysician assessmentPrompt testingDetermination of heartChatGPTDesign frameworkNote analysisHeartSubscoresSimulated patientsClinical spaceThe Scope of Multimorbidity in Family Medicine: Identifying Age Patterns Across the Lifespan
Chartash D, Gilson A, Taylor R, Hart L. The Scope of Multimorbidity in Family Medicine: Identifying Age Patterns Across the Lifespan. The Journal Of The American Board Of Family Medicine 2024, 37: 251-260. PMID: 38740476, DOI: 10.3122/jabfm.2023.230221r1.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsRates of multimorbidityICD-10 diagnostic codesFamily medicine clinicPresence of multimorbidityHealth care systemCardiometabolic disordersMedical historyStudy periodMultimorbidity rateMultimorbidity indexGroup of diagnosesPatient transitionsFamily medicineGeriatric careRetrospective cohort studyCare systemMental healthMultimorbidityMedicine clinicDiagnostic codesPractical resourcesAlcohol use disorderCohort studyAged 0Age groupsCorrection: How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessment
Gilson A, Safranek C, Huang T, Socrates V, Chi L, Taylor R, Chartash D. Correction: How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessment. JMIR Medical Education 2024, 10: e57594. PMID: 38412478, PMCID: PMC10933712, DOI: 10.2196/57594.Peer-Reviewed Original ResearchCitationsAltmetricAlgorithms in medical decision-making and in everyday life: what’s the difference?
Chartash D, Bruno M. Algorithms in medical decision-making and in everyday life: what’s the difference? Diagnosis 2024, 0 PMID: 38386866, DOI: 10.1515/dx-2024-0010.Peer-Reviewed Original Research
2023
Computational phenotypes for patients with opioid-related disorders presenting to the emergency department
Taylor R, Gilson A, Schulz W, Lopez K, Young P, Pandya S, Coppi A, Chartash D, Fiellin D, D’Onofrio G. Computational phenotypes for patients with opioid-related disorders presenting to the emergency department. PLOS ONE 2023, 18: e0291572. PMID: 37713393, PMCID: PMC10503758, DOI: 10.1371/journal.pone.0291572.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSubstance use disordersUse disordersED visitsPatient presentationCarlson comorbidity indexOpioid-related diagnosesOpioid-related disordersOne-year survivalRate of medicationOpioid use disorderElectronic health record dataPatient-oriented outcomesYears of ageHealth record dataChronic substance use disordersED returnComorbidity indexAcute overdoseMedical managementClinical entityRetrospective studyEmergency departmentChronic conditionsInclusion criteriaUnique cohortThe Role of Large Language Models in Medical Education: Applications and Implications
Safranek C, Sidamon-Eristoff A, Gilson A, Chartash D. The Role of Large Language Models in Medical Education: Applications and Implications. JMIR Medical Education 2023, 9: e50945. PMID: 37578830, PMCID: PMC10463084, DOI: 10.2196/50945.Peer-Reviewed Original ResearchCitationsAltmetricConceptsMedical educationCore Entrustable Professional ActivitiesMedical education communityEntrustable professional activitiesPreclinical curriculumEducation communityMedical schoolsMedical studentsProfessional activityStudentsEducationPractice casesLearningMedical knowledgeInsufficient abilityInterpersonal interactionsExtensive discourseHealth care landscapeImmersive interactionCare landscapeCurriculumImminent roleSchoolsBrainstormingNonverbal cuesA pipeline for the retrieval and extraction of domain-specific information with application to COVID-19 immune signatures
Newton A, Chartash D, Kleinstein S, McDougal R. A pipeline for the retrieval and extraction of domain-specific information with application to COVID-19 immune signatures. BMC Bioinformatics 2023, 24: 292. PMID: 37474900, PMCID: PMC10357743, DOI: 10.1186/s12859-023-05397-8.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsDomain-specific informationDocument embeddingsSVM classifierSemi-structured representationsTraining setWeb-based formKnowledge repositoryInformation modelAutomatic analysisClassifier predictionsClassifierSignature informationAutomated systemBiomedical publicationsPaper authorsEmbeddingIncomplete information modelLiterature miningIterative processSpecific informationSuch informationInformationLimited setSetQueriesAuthors’ Reply to: Variability in Large Language Models’ Responses to Medical Licensing and Certification Examinations
Gilson A, Safranek C, Huang T, Socrates V, Chi L, Taylor R, Chartash D. Authors’ Reply to: Variability in Large Language Models’ Responses to Medical Licensing and Certification Examinations. JMIR Medical Education 2023, 9: e50336. PMID: 37440299, PMCID: PMC10375396, DOI: 10.2196/50336.Peer-Reviewed Original ResearchCitationsAltmetric
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Yale School of Medicine
100 College Street
New Haven, CT 06511
United States