Tina L Doshi

46 total papers · 817 total citations
28 papers, 482 citations indexed

About

Tina L Doshi is a scholar working on Physiology, Pathology and Forensic Medicine and Pharmacology. According to data from OpenAlex, Tina L Doshi has authored 28 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Physiology, 10 papers in Pathology and Forensic Medicine and 9 papers in Pharmacology. Recurrent topics in Tina L Doshi's work include Pain Mechanisms and Treatments (11 papers), Musculoskeletal pain and rehabilitation (8 papers) and Spine and Intervertebral Disc Pathology (6 papers). Tina L Doshi is often cited by papers focused on Pain Mechanisms and Treatments (11 papers), Musculoskeletal pain and rehabilitation (8 papers) and Spine and Intervertebral Disc Pathology (6 papers). Tina L Doshi collaborates with scholars based in United States, Thailand and Canada. Tina L Doshi's co-authors include Michael Lim, Alice Hung, Mark C. Bicket, Srinivasa N. Raja, Claudia M. Campbell, Steven P. Cohen, Eric J. Wang, Nuj Tontisirin, Connie Kurihara and Paul F. Pasquina and has published in prestigious journals such as SHILAP Revista de lepidopterología, Neurology and Pain.

In The Last Decade

Tina L Doshi

27 papers receiving 476 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Tina L Doshi	172	152	120	90	81	28	482
Jordi Pérez	125 0.7×	172 1.1×	52 0.4×	85 0.9×	85 1.0×	49	476
Nicholas Shenker	160 0.9×	161 1.1×	63 0.5×	42 0.5×	117 1.4×	37	500
Dajie Wang	105 0.6×	117 0.8×	127 1.1×	201 2.2×	104 1.3×	43	549
Karina Charipova	80 0.5×	137 0.9×	71 0.6×	198 2.2×	83 1.0×	42	544
Dermot P. Maher	99 0.6×	134 0.9×	46 0.4×	157 1.7×	167 2.1×	32	515
P.M. Finch	141 0.8×	156 1.0×	80 0.7×	106 1.2×	145 1.8×	18	411
Mariam Salisu Orhurhu	80 0.5×	148 1.0×	79 0.7×	189 2.1×	86 1.1×	23	484
Kelly R. Murphy	79 0.5×	129 0.8×	87 0.7×	91 1.0×	125 1.5×	25	451
Ke Ma	103 0.6×	143 0.9×	69 0.6×	63 0.7×	58 0.7×	38	405
Michael S. Leong	197 1.1×	106 0.7×	65 0.5×	88 1.0×	277 3.4×	26	513

Countries citing papers authored by Tina L Doshi

Since Specialization

Citations

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

Fields of papers citing papers by Tina L Doshi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tina L Doshi

This figure shows the co-authorship network connecting the top 25 collaborators of Tina L Doshi. A scholar is included among the top collaborators of Tina L 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 Tina L Doshi. Tina L 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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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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