Jayesh Mehta

13.2k total citations · 1 hit paper
226 papers, 8.3k citations indexed

About

Jayesh Mehta is a scholar working on Hematology, Oncology and Epidemiology. According to data from OpenAlex, Jayesh Mehta has authored 226 papers receiving a total of 8.3k indexed citations (citations by other indexed papers that have themselves been cited), including 152 papers in Hematology, 81 papers in Oncology and 34 papers in Epidemiology. Recurrent topics in Jayesh Mehta's work include Hematopoietic Stem Cell Transplantation (92 papers), Multiple Myeloma Research and Treatments (58 papers) and Acute Myeloid Leukemia Research (45 papers). Jayesh Mehta is often cited by papers focused on Hematopoietic Stem Cell Transplantation (92 papers), Multiple Myeloma Research and Treatments (58 papers) and Acute Myeloid Leukemia Research (45 papers). Jayesh Mehta collaborates with scholars based in United States, United Kingdom and Philippines. Jayesh Mehta's co-authors include Seema Singhal, Nikhil C. Munshi, Bart Barlogie, David S. Siegel, R Powles, Raman Desikan, Madhav V. Dhodapkar, Elias Anaissie, John Crowley and Carla S. Wilson and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Oncology and Blood.

In The Last Decade

Jayesh Mehta

218 papers receiving 8.1k citations

Hit Papers

Antitumor Activity of Thalidomide in Refractory Multiple ... 1999 2026 2008 2017 1999 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jayesh Mehta United States 46 4.9k 2.8k 2.7k 1.3k 1.1k 226 8.3k
Gary J. Schiller United States 51 6.2k 1.3× 2.4k 0.9× 3.3k 1.2× 1.3k 1.0× 1.2k 1.1× 382 10.3k
Emmanuel Raffoux France 47 4.4k 0.9× 1.7k 0.6× 3.0k 1.1× 1.0k 0.8× 797 0.7× 193 7.7k
Hwei‐Fang Tien Taiwan 49 3.9k 0.8× 1.6k 0.6× 2.8k 1.0× 1.3k 1.0× 480 0.4× 299 7.9k
David H. Vesole United States 43 6.5k 1.3× 4.4k 1.5× 4.3k 1.6× 1.6k 1.2× 1.5k 1.4× 210 10.3k
Anna Dmoszyńska Poland 39 3.8k 0.8× 3.0k 1.0× 2.9k 1.1× 626 0.5× 642 0.6× 207 8.0k
Renato Fanin Italy 42 3.6k 0.7× 2.0k 0.7× 1.4k 0.5× 665 0.5× 354 0.3× 226 6.6k
Rajesh Chopra United Kingdom 48 3.2k 0.7× 2.8k 1.0× 2.6k 0.9× 720 0.6× 403 0.4× 171 8.9k
Takanori Teshima Japan 52 5.6k 1.1× 2.5k 0.9× 1.8k 0.7× 1.1k 0.8× 556 0.5× 486 10.6k
E. Thiel Germany 46 2.1k 0.4× 1.7k 0.6× 1.4k 0.5× 1.3k 1.0× 1.2k 1.0× 208 6.9k
Shinji Nakao Japan 49 3.7k 0.7× 1.5k 0.5× 1.4k 0.5× 918 0.7× 543 0.5× 443 8.4k

Countries citing papers authored by Jayesh Mehta

Since Specialization
Citations

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

Fields of papers citing papers by Jayesh Mehta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jayesh Mehta

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

All Works

20 of 20 papers shown
2.
Trifilio, Steven, Alfred Rademaker, Jayesh Mehta, et al.. (2011). Mitoxantrone and etoposide with or without intermediate dose cytarabine for the treatment of primary induction failure or relapsed acute myeloid leukemia. Leukemia Research. 36(4). 394–396. 25 indexed citations
3.
Krishnamurthy, Jairam, Richard Meagher, Andrew M. Evens, et al.. (2008). Actual or ideal body weight to calculate CD34+ cell dose in patients undergoing autologous hematopoietic SCT for myeloma?. Bone Marrow Transplantation. 43(4). 301–305. 5 indexed citations
5.
Verma, Amit, Steven Trifilio, Seema Singhal, et al.. (2004). How long after neutrophil recovery should myeloid growth factors be continued in autologous hematopoietic stem cell transplant recipients?. Bone Marrow Transplantation. 33(7). 715–719. 4 indexed citations
6.
Trifilio, Steven, Anita Verma, & Jayesh Mehta. (2004). Antimicrobial prophylaxis in hematopoietic stem cell transplant recipients: heterogeneity of current clinical practice. Bone Marrow Transplantation. 33(7). 735–739. 48 indexed citations
7.
Verma, Amit, Matthew Doyle, Lisa Boggio, et al.. (2004). Can the stem cell mobilization technique influence CD34+ cell collection efficiency of leukapheresis procedures in patients with hematologic malignancies?. Bone Marrow Transplantation. 35(3). 243–246. 31 indexed citations
9.
Gordon, Leo I., Seema Singhal, Martin S. Tallman, et al.. (2003). Ideal or actual body weight to calculate CD34+ cell doses for allogeneic hematopoietic stem cell transplantation?. Bone Marrow Transplantation. 33(2). 161–164. 18 indexed citations
10.
Mehta, Jayesh, et al.. (2002). Thalidomide in cancer. Biomedicine & Pharmacotherapy. 56(1). 4–12. 99 indexed citations
11.
Mehta, Jayesh, R Powles, Bhawna Sirohi, et al.. (2002). Does donor–recipient ABO incompatibility protect against relapse after allogeneic bone marrow transplantation in first remission acute myeloid leukemia?. Bone Marrow Transplantation. 29(10). 853–859. 32 indexed citations
13.
Kulkarni, Shashikant, R Powles, Jayesh Mehta, et al.. (1998). Thalidomide in GVHD - S anti-GVHD effect separable from the antiangiogenesis?. Blood. 92(10). 4 indexed citations
14.
Mehta, Jayesh, Guido Tricot, Sundar Jagannath, et al.. (1998). Salvage autologous or allogeneic transplantation for multiple myeloma refractory to or relapsing after a first-line autograft?. Bone Marrow Transplantation. 21(9). 887–892. 101 indexed citations
15.
Kulkarni, Shashikant, R Powles, Jayesh Mehta, et al.. (1997). Thalidomide is very effective for chronic GVHD but has no activity in acute GVHD.. Blood. 90(10). 1673–1673. 2 indexed citations
16.
Mehta, Jayesh, Patrick Chu, R Powles, et al.. (1997). Amphotericin B lipid complex (ABLC) for the treatment of confirmed or presumed fungal infections in immunocompromised patients with hematologic malignancies. Bone Marrow Transplantation. 20(1). 39–43. 52 indexed citations
17.
Treleaven, J, R Powles, S Kulkarni, et al.. (1996). Autografting with CD52 monoclonal antibody-purged marrow for acute lymphoblastic leukemia.. Blood. 88. 1009–1009. 2 indexed citations
18.
Kapelushnik, Joseph, Dan Engelhard, Jayesh Mehta, et al.. (1995). Sequential respiratory syncytial virus cytomegalovirus pneumonia following bone marrow transplantation. Journal of Medical Virology. 46(2). 169–171. 4 indexed citations
19.
Kapelushnik, Joseph, Arnon Nagler, E Naparstek, et al.. (1993). Autologous bone marrow transplantation for stage IV neuroblastoma: the role of soybean agglutinin purging.. PubMed. 25(3). 2375–6. 5 indexed citations
20.
Treleaven, Jennifer & Jayesh Mehta. (1992). Bone Marrow and Peripheral Blood Stem Cell Harvesting. Journal of Hematotherapy. 1(3). 215–223. 10 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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