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Morgan Cheatham

Morgan Cheatham has 2 papers in our library, in 2023, most of them on Evaluation & benchmarks; often with Akshay Swaminathan, Rahul Thapa.

2 papers in our library · 2023

OpenAlex · ORCID · h-index 6 · 6 works · 187 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 119 times in our library · ⭐ Paper Stars ranking: #825

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Mississippi State UniversityStarkville · United States2022–2024 · 4 paperscurrent🎓Brown UniversityProvidence · United States2023–2024 · 2 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksMedicine · 2 worksHealth Informatics · 2 worksInformation Systems · 1 workPublic Health, Environmental and Occupational Health · 1 workArtificial Intelligence · 1 workHealth Information Management · 1 workHealth Professions · 1 work

🧭 Topics 1Research subjects and languages the work is about.Evaluation & benchmarks · 1 work

💡 Concepts 2Key ideas and methods explained on our concept pages.Language model · 1 workLarge language models · 1 work

 Works by year

2020s

20232 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models (2023 · 4,173 citations)
    The authors asked whether a general-purpose large language model, never tuned for medicine, could handle the United States Medical Licensing Exam (USMLE), a three-part licensing test (Step 1, Step 2CK, Step 3) that combines basic science, clinical reasoning, management and ethics.
  2. Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery (2023 · 44 citations)
    Most tests of medical LLMs rely on exam-style benchmarks, which say little about real clinical use. This study asks whether GPT-3.5 and GPT-4 can safely and usefully answer questions physicians actually raised during patient care. The authors drew on questions sent to a Stanford informatics consultation service…

 Co-authors here

2 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 119 times (of the 149,439 papers whose bibliographies we read); 38 citing papers with a page here →.

Updated

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