Vimig Socrates

2.3k total citations · 1 hit paper
17 papers, 1.4k citations indexed

About

Vimig Socrates is a scholar working on Artificial Intelligence, Health Informatics and Molecular Biology. According to data from OpenAlex, Vimig Socrates has authored 17 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 6 papers in Health Informatics and 4 papers in Molecular Biology. Recurrent topics in Vimig Socrates's work include Machine Learning in Healthcare (7 papers), Artificial Intelligence in Healthcare and Education (6 papers) and Biomedical Text Mining and Ontologies (4 papers). Vimig Socrates is often cited by papers focused on Machine Learning in Healthcare (7 papers), Artificial Intelligence in Healthcare and Education (6 papers) and Biomedical Text Mining and Ontologies (4 papers). Vimig Socrates collaborates with scholars based in United States and Ireland. Vimig Socrates's co-authors include Thomas Huang, Richard A. Taylor, Conrad Safranek, David Chartash, Ling Chi, Aidan Gilson, Allan Fong, Bidisha Nath, Richard Goldstein and Raj M. Ratwani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Medical Internet Research and Journal of the American Medical Informatics Association.

In The Last Decade

Vimig Socrates

14 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessment

2023 1.3k citations Aidan Gilson, Conrad Safranek et al. JMIR Medical Education profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Vimig Socrates United States	7	1.1k	539	426	189	156	17	1.4k
David Chartash United States	8	1.1k 1.0×	549 1.0×	420 1.0×	190 1.0×	169 1.1×	25	1.4k
Thomas Huang United States	6	1.1k 1.0×	535 1.0×	412 1.0×	186 1.0×	129 0.8×	13	1.4k
Aidan Gilson United States	4	1.1k 1.0×	533 1.0×	406 1.0×	185 1.0×	130 0.8×	14	1.3k
Conrad Safranek United States	6	1.1k 1.0×	535 1.0×	410 1.0×	186 1.0×	133 0.9×	18	1.4k
Adam Poliak United States	11	818 0.7×	303 0.6×	607 1.4×	136 0.7×	169 1.1×	24	1.6k
Tirth Dave Ukraine	7	739 0.6×	317 0.6×	292 0.7×	90 0.5×	99 0.6×	43	1.1k
Tiffany H. Kung United States	8	1.7k 1.5×	888 1.6×	712 1.7×	268 1.4×	229 1.5×	10	2.3k
Michael Hogarth United States	15	879 0.8×	387 0.7×	550 1.3×	155 0.8×	238 1.5×	58	1.7k
Joseph Petro United States	4	683 0.6×	300 0.6×	322 0.8×	85 0.4×	108 0.7×	6	954
Sumaya N. Almohareb Saudi Arabia	4	617 0.5×	271 0.5×	294 0.7×	45 0.2×	137 0.9×	15	1.3k

Countries citing papers authored by Vimig Socrates

Since Specialization

Citations

This map shows the geographic impact of Vimig Socrates's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Vimig Socrates with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vimig Socrates more than expected).

Fields of papers citing papers by Vimig Socrates

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vimig Socrates. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Vimig Socrates. The network helps show where Vimig Socrates may publish in the future.

Co-authorship network of co-authors of Vimig Socrates

This figure shows the co-authorship network connecting the top 25 collaborators of Vimig Socrates. A scholar is included among the top collaborators of Vimig Socrates based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Vimig Socrates. Vimig Socrates is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Huang, Thomas, Vimig Socrates, Conrad Safranek, et al.. (2025). Characterizing Emergency Department Care for Patients With Histories of Incarceration. Journal of the American College of Emergency Physicians Open. 6(1). 100022–100022.

Socrates, Vimig, D. Wright, Thomas Huang, et al.. (2025). Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study. JMIR Aging. 8. e69504–e69504. 1 indexed citations

Wright, D., Vimig Socrates, Thomas Huang, et al.. (2025). Automated computation of the HEART score with the GPT-4 large language model. The American Journal of Emergency Medicine. 93. 120–125.

Moore, Christopher, et al.. (2025). Using natural language processing to identify emergency department patients with incidental lung nodules requiring follow‐up. Academic Emergency Medicine. 32(3). 274–283. 2 indexed citations

Socrates, Vimig, et al.. (2024). HEART: Learning better representation of EHR data with a heterogeneous relation-aware transformer. Journal of Biomedical Informatics. 159. 104741–104741. 1 indexed citations

Socrates, Vimig, Aidan Gilson, Ling Chi, et al.. (2024). Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models. Academic Emergency Medicine. 31(6). 599–610. 5 indexed citations

Huang, Thomas, Conrad Safranek, Vimig Socrates, et al.. (2024). Patient-Representing Population's Perceptions of GPT-Generated Versus Standard Emergency Department Discharge Instructions: Randomized Blind Survey Assessment. Journal of Medical Internet Research. 26. e60336–e60336. 11 indexed citations

Taylor, Robert A., Rohit B. Sangal, Adrian D. Haimovich, et al.. (2024). Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions. Academic Emergency Medicine. 32(3). 327–339. 12 indexed citations

Safranek, Conrad, Thomas Huang, D. Wright, et al.. (2024). Automated HEART score determination via ChatGPT: Honing a framework for iterative prompt development. SHILAP Revista de lepidopterología. 5(2). e13133–e13133. 8 indexed citations

10.

Huang, Thomas, Vimig Socrates, Aidan Gilson, et al.. (2024). Identifying incarceration status in the electronic health record using large language models in emergency department settings. Journal of Clinical and Translational Science. 8(1). e53–e53. 5 indexed citations

11.

Socrates, Vimig, et al.. (2023). Predicting relations between SOAP note sections: The value of incorporating a clinical information model. Journal of Biomedical Informatics. 141. 104360–104360.

12.

Gilson, Aidan, Conrad Safranek, Thomas Huang, et al.. (2023). Authors’ Reply to: Variability in Large Language Models’ Responses to Medical Licensing and Certification Examinations. JMIR Medical Education. 9. e50336–e50336. 2 indexed citations

13.

Gilson, Aidan, Conrad Safranek, Thomas Huang, et al.. (2023). 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. 9. e45312–e45312. 1275 indexed citations breakdown →

14.

Socrates, Vimig. (2022). Extraction of Diagnostic Reasoning Relations for Clinical Knowledge Graphs. 413–421. 2 indexed citations

15.

Melnick, Edward R., Allan Fong, Vimig Socrates, et al.. (2021). Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis. Journal of the American Medical Informatics Association. 28(7). 1383–1392. 45 indexed citations

16.

Kim, Matthew, et al.. (2017). ProvCaRe Semantic Provenance Knowledgebase: Evaluating Scientific Reproducibility of Research Studies.. PubMed. 2017. 1705–1714. 7 indexed citations

17.

Socrates, Vimig, et al.. (2017). Towards transforming FDA adverse event narratives into actionable structured data for improved pharmacovigilance. 777–782. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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