Matthew Varugheese

501 total citations
8 papers, 213 citations indexed

About

Matthew Varugheese is a scholar working on Genetics, Molecular Biology and Health Information Management. According to data from OpenAlex, Matthew Varugheese has authored 8 papers receiving a total of 213 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Genetics, 4 papers in Molecular Biology and 2 papers in Health Information Management. Recurrent topics in Matthew Varugheese's work include Genomics and Rare Diseases (5 papers), Biomedical Text Mining and Ontologies (3 papers) and BRCA gene mutations in cancer (2 papers). Matthew Varugheese is often cited by papers focused on Genomics and Rare Diseases (5 papers), Biomedical Text Mining and Ontologies (3 papers) and BRCA gene mutations in cancer (2 papers). Matthew Varugheese collaborates with scholars based in United States. Matthew Varugheese's co-authors include Samuel Aronson, Samantha Baxter, Heidi L. Rehm, Lawrence Babb, Eugene Clark, Lisa P. Newmark, Benjamin M. Scirica, Lisa Farwell, Kavishwar B. Wagholikar and Pamela M. Neri and has published in prestigious journals such as JAMA, Journal of the American Medical Informatics Association and Human Mutation.

In The Last Decade

Matthew Varugheese

8 papers receiving 209 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew Varugheese United States	7	129	66	46	38	28	8	213
Shang Xue China	5	42 0.3×	48 0.7×	31 0.7×	10 0.3×	53 1.9×	9	238
Grant M. Wood United States	7	59 0.5×	45 0.7×	13 0.3×	24 0.6×	22 0.8×	14	151
Gabrielle Bertier France	6	75 0.6×	36 0.5×	37 0.8×	41 1.1×	10 0.4×	14	169
David Glazer Canada	4	187 1.4×	91 1.4×	51 1.1×	127 3.3×	35 1.3×	7	343
Moustafa Abdalla United States	7	26 0.2×	78 1.2×	12 0.3×	22 0.6×	30 1.1×	18	200
Haley Hunter-Zinck United States	4	79 0.6×	49 0.7×	31 0.7×	6 0.2×	15 0.5×	4	171
Verónica Dávila‐Batista Spain	8	21 0.2×	64 1.0×	55 1.2×	65 1.7×	16 0.6×	12	258
J. Gray United States	8	24 0.2×	64 1.0×	39 0.8×	21 0.6×	25 0.9×	15	203
Eugene Clark United States	5	130 1.0×	82 1.2×	49 1.1×	23 0.6×	5 0.2×	5	206
Anand Thakarakkattil Narayanan Nair United Kingdom	8	79 0.6×	86 1.3×	8 0.2×	17 0.4×	20 0.7×	8	329

Countries citing papers authored by Matthew Varugheese

Since Specialization

Citations

This map shows the geographic impact of Matthew Varugheese'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 Matthew Varugheese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Varugheese more than expected).

Fields of papers citing papers by Matthew Varugheese

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Varugheese. 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 Matthew Varugheese. The network helps show where Matthew Varugheese may publish in the future.

Co-authorship network of co-authors of Matthew Varugheese

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Varugheese. A scholar is included among the top collaborators of Matthew Varugheese 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 Matthew Varugheese. Matthew Varugheese is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Ünlü, Ozan, Matthew Varugheese, Fei Wang, et al.. (2025). Manual vs AI-Assisted Prescreening for Trial Eligibility Using Large Language Models—A Randomized Clinical Trial. JAMA. 333(12). 1084–1084. 5 indexed citations

2.

Ünlü, Ozan, Matthew Varugheese, Kavishwar B. Wagholikar, et al.. (2024). Retrieval-Augmented Generation–Enabled GPT-4 for Clinical Trial Screening. NEJM AI. 1(7). 32 indexed citations

3.

Aronson, Samuel, Benjamin M. Scirica, William J. Gordon, et al.. (2021). Workflow Automation for a Virtual Hypertension Management Program. Applied Clinical Informatics. 12(5). 1041–1048. 13 indexed citations

4.

Volk, Lynn A., Lisa P. Newmark, Matthew Varugheese, et al.. (2016). Evaluation: A Qualitative Pilot Study of Novel Information Technology Infrastructure to Communicate Genetic Variant Updates. Applied Clinical Informatics. 7(2). 461–476. 9 indexed citations

5.

Wilcox, Allison R., Pamela M. Neri, Lynn A. Volk, et al.. (2013). A novel clinician interface to improve clinician access to up-to-date genetic results. Journal of the American Medical Informatics Association. 21(e1). e117–e121. 13 indexed citations

6.

Neri, Pamela M., Lynn A. Volk, Lisa P. Newmark, et al.. (2012). Usability of a novel clinician interface for genetic results. Journal of Biomedical Informatics. 45(5). 950–957. 22 indexed citations

7.

Aronson, Samuel, Eugene Clark, Matthew Varugheese, et al.. (2012). Communicating new knowledge on previously reported genetic variants. Genetics in Medicine. 14(8). 713–719. 66 indexed citations

8.

Aronson, Samuel, Eugene Clark, Lawrence Babb, et al.. (2011). The GeneInsight suite: a platform to support laboratory and provider use of DNA-based genetic testing. Human Mutation. 32(5). 532–536. 53 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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