Rushabh Doshi

680 total citations
21 papers, 380 citations indexed

About

Rushabh Doshi is a scholar working on General Health Professions, Health Informatics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Rushabh Doshi has authored 21 papers receiving a total of 380 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in General Health Professions, 6 papers in Health Informatics and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Rushabh Doshi's work include Artificial Intelligence in Healthcare and Education (6 papers), Radiology practices and education (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Rushabh Doshi is often cited by papers focused on Artificial Intelligence in Healthcare and Education (6 papers), Radiology practices and education (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Rushabh Doshi collaborates with scholars based in United States, Bulgaria and Sri Lanka. Rushabh Doshi's co-authors include Kanhai Amin, P.K. Khosla, Howard P. Forman, Simar S. Bajaj, Reem Z. Sharaiha, Michel Kahaleh, Amit P. Desai, Amy Tyberg, Moamen Gabr and Monica Gaidhane and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Radiology.

In The Last Decade

Rushabh Doshi

18 papers receiving 374 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rushabh Doshi United States	8	146	139	115	109	85	21	380
Ramya Yethadka India	7	84 0.6×	103 0.7×	102 0.9×	43 0.4×	83 1.0×	26	323
Judy Burleson United States	12	42 0.3×	62 0.4×	257 2.2×	83 0.8×	34 0.4×	22	465
Marthe Larsen Norway	11	73 0.5×	69 0.5×	248 2.2×	142 1.3×	208 2.4×	35	420
Melissa H. Coleman United States	9	63 0.4×	71 0.5×	38 0.3×	41 0.4×	30 0.4×	13	314
Eyal Shachar Israel	8	54 0.4×	112 0.8×	70 0.6×	29 0.3×	72 0.8×	18	248
Elizabeth Cottrill United States	8	95 0.7×	50 0.4×	57 0.5×	21 0.2×	33 0.4×	32	255
Emilio Madrigal United States	11	63 0.4×	29 0.2×	67 0.6×	52 0.5×	76 0.9×	26	273
Natalie Gangai United States	11	81 0.6×	18 0.1×	165 1.4×	118 1.1×	34 0.4×	42	318
Dara Bracken‐Clarke United States	7	26 0.2×	93 0.7×	63 0.5×	57 0.5×	73 0.9×	19	351
Avery Smith United States	4	32 0.2×	140 1.0×	58 0.5×	101 0.9×	120 1.4×	11	354

Countries citing papers authored by Rushabh Doshi

Since Specialization

Citations

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

Fields of papers citing papers by Rushabh Doshi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rushabh Doshi

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

All Works

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20 of 20 papers shown

Chapman, Kenneth B., et al.. (2025). Spinal cord stimulator utilization trends and predictors of unsuccessful trial-to-implant conversion. North American Spine Society Journal (NASSJ). 22. 100616–100616. 2 indexed citations

Jain, Pankaj, et al.. (2025). Digital Health: An Opportunity to Advance Health Equity for People With Disabilities. Milbank Quarterly. 103(4). 966–987. 1 indexed citations

AlAshqar, Abdelrahman, et al.. (2025). Comparative Evaluation of Artificial Intelligence Models for Contraceptive Counseling. SHILAP Revista de lepidopterología. 5(2). 10–10. 2 indexed citations

Shahjalal, Md., et al.. (2025). Shared decision-making in cancer care in Bangladesh: evidence from a resource-constrained setting. Journal of Cancer Research and Clinical Oncology. 151(12). 310–310.

Doshi, Rushabh, Kanhai Amin, Simar S. Bajaj, et al.. (2025). Development, optimization, and preliminary evaluation of a novel artificial intelligence tool to promote patient health literacy in radiology reports: The Rads-Lit tool. PLoS ONE. 20(9). e0331368–e0331368.

Spatz, Erica S., et al.. (2025). Accountable Care Organization Participation and Cardiovascular Care Quality. JAMA Cardiology. 10(6). 545–545.

Doshi, Rushabh, Kanhai Amin, P.K. Khosla, et al.. (2024). Quantitative Evaluation of Large Language Models to Streamline Radiology Report Impressions: A Multimodal Retrospective Analysis. Radiology. 310(3). e231593–e231593. 56 indexed citations

Khosla, P.K., Kanhai Amin, & Rushabh Doshi. (2024). Combating Chronic Disease with Barbershop Health Interventions: AReview of Current Knowledge and Potential for Big Data. The Yale Journal of Biology and Medicine. 97(2). 239–245. 2 indexed citations

Amin, Kanhai, Linda C. Mayes, P.K. Khosla, & Rushabh Doshi. (2024). Assessing the Efficacy of Large Language Models in Health Literacy: AComprehensive Cross-Sectional Study. The Yale Journal of Biology and Medicine. 97(1). 17–27. 19 indexed citations

10.

Amin, Kanhai, et al.. (2024). Comparative Readability Assessment of Four Large Language Models in Answers to Common Contraception Questions [ID 2683638]. Obstetrics and Gynecology. 143(5S). 12S–12S. 1 indexed citations

11.

Amin, Kanhai, Melissa Davis, Rushabh Doshi, et al.. (2023). Accuracy of ChatGPT, Google Bard, and Microsoft Bing for Simplifying Radiology Reports. Radiology. 309(2). e232561–e232561. 60 indexed citations

12.

Amin, Kanhai, P.K. Khosla, Rushabh Doshi, Sophie Chheang, & Howard P. Forman. (2023). Artificial Intelligence to Improve Patient Understanding of RadiologyReports. The Yale Journal of Biology and Medicine. 96(3). 407–417. 31 indexed citations

13.

Amin, Kanhai, Rushabh Doshi, & Howard P. Forman. (2023). Large language models as a source of health information: Are they patient-centered? A longitudinal analysis. Healthcare. 12(1). 100731–100731. 11 indexed citations

14.

Dewasurendra, Rajika, Mary Lynn Baniecki, S. F. Schaffner, et al.. (2020). Use of a Plasmodium vivax genetic barcode for genomic surveillance and parasite tracking in Sri Lanka. Malaria Journal. 19(1). 342–342. 7 indexed citations

15.

Kumta, Nikhil A., Rushabh Doshi, Louis J. Aronne, & Reem Z. Sharaiha. (2016). Trimming the fat: endoscopic suturing for tightening of prior endoscopic sleeve gastroplasty. Gastrointestinal Endoscopy. 85(1). 253–254. 8 indexed citations

16.

Kumta, Nikhil A., et al.. (2016). Retrieval and reuse of a dislodged lumen-apposing metal stent during endoscopic necrosectomy for pancreatic necrosis. Gastrointestinal Endoscopy. 84(2). 364–364. 4 indexed citations

17.

Tyberg, Amy, Kunal Karia, Moamen Gabr, et al.. (2016). Management of pancreatic fluid collections: A comprehensive review of the literature. World Journal of Gastroenterology. 22(7). 2256–2270. 129 indexed citations

18.

Doshi, Rushabh, et al.. (2016). EUS-guided pancreatic drainage for recurrent pancreatitis. Gastrointestinal Endoscopy. 84(1). 186–187. 1 indexed citations

19.

Kumta, Nikhil A., Amit P. Desai, Rushabh Doshi, Michel Kahaleh, & Reem Z. Sharaiha. (2016). Endoscopic mucosal resection of duodenal carcinoid. Endoscopy. 48(S 01). E158–E159. 3 indexed citations

20.

Doshi, Rushabh, et al.. (1991). Declining necropsy rate.. Journal of Clinical Pathology. 44(11). 964.2–965. 1 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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