---
title: "Morgan Cheatham — author profile and papers in our library"
description: "Morgan Cheatham, Brown University: 2 papers on Elamur Research (2023), h-index 6 — affiliations, topics, co-authors and who cites them in…"
canonical: "https://research.elamur.ai/free/en/authors/morgan-cheatham/"
---
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# Morgan Cheatham

Morgan Cheatham has 2 papers in our library, in 2023, most of them on [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Akshay Swaminathan](https://md.research.elamur.ai/free/en/authors/akshay-swaminathan/), [Rahul Thapa](https://md.research.elamur.ai/free/en/authors/rahul-thapa/).

2 papers in our library · 2023

[OpenAlex](https://openalex.org/A5060434411) · [ORCID](https://orcid.org/0000-0001-6709-8119) · [**h-index 6**](https://openalex.org/authors/A5060434411) · [6 works](https://openalex.org/works?filter=author.id:A5060434411) · [187 citations](https://openalex.org/works?filter=author.id:A5060434411&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/morgan-cheatham/#papers) · [🔗 Cited 119 times in our library](https://md.research.elamur.ai/free/en/authors/morgan-cheatham/cited-by/) · [⭐ Paper Stars ranking: #825](https://md.research.elamur.ai/free/en/paper-stars/page/9/#star-825)

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

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Morgan+Cheatham) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Morgan+Cheatham) · [dblp](https://dblp.org/search?q=Morgan+Cheatham) · [ACL Anthology](https://aclanthology.org/search/?q=Morgan+Cheatham)

## Affiliations

[🎓**Mississippi State University** Starkville · United States 2022–2024 · 4 papers*current*](https://ror.org/0432jq872) · [🎓**Brown University** Providence · United States 2023–2024 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/brown-university/)

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 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Medicine · 2 works](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Health Informatics · 2 works](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Public Health, Environmental and Occupational Health · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/public-health-environmental-and-occupational-health/) · [Artificial Intelligence · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Health Information Management · 1 work](https://md.research.elamur.ai/free/en/shelves/health-professions/health-information-management/) · [Health Professions · 1 work](https://md.research.elamur.ai/free/en/shelves/health-professions/)

🧭 Topics 1 Research subjects and languages the work is about.[Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/)

💡 Concepts 2 Key ideas and methods explained on our concept pages.[Language model · 1 work](https://md.research.elamur.ai/free/en/concepts/language-model/) · [Large language models · 1 work](https://md.research.elamur.ai/free/en/concepts/large-language-models/)

## Works by year

### 2020s

[**2023** 2 papers](https://md.research.elamur.ai/free/en/authors/morgan-cheatham/year/2023/)

## 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](https://md.research.elamur.ai/free/en/papers/kung-2023-performance-chatgpt-usmle-potential-ai/)** *(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](https://md.research.elamur.ai/free/en/papers/dash-2023-evaluation-gpt-3-5-gpt/)** *(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.

- [Akshay Swaminathan](https://md.research.elamur.ai/free/en/authors/akshay-swaminathan/)
- [Rahul Thapa](https://md.research.elamur.ai/free/en/authors/rahul-thapa/)

## Venues

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

- PLOS Digital Health

## 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 →](https://md.research.elamur.ai/free/en/authors/morgan-cheatham/cited-by/).

Updated 3 November 2026
