Keyur P. Patel

25.5k total citations
334 papers, 8.6k citations indexed

About

Keyur P. Patel is a scholar working on Hematology, Genetics and Molecular Biology. According to data from OpenAlex, Keyur P. Patel has authored 334 papers receiving a total of 8.6k indexed citations (citations by other indexed papers that have themselves been cited), including 185 papers in Hematology, 141 papers in Genetics and 85 papers in Molecular Biology. Recurrent topics in Keyur P. Patel's work include Acute Myeloid Leukemia Research (151 papers), Chronic Lymphocytic Leukemia Research (70 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (70 papers). Keyur P. Patel is often cited by papers focused on Acute Myeloid Leukemia Research (151 papers), Chronic Lymphocytic Leukemia Research (70 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (70 papers). Keyur P. Patel collaborates with scholars based in United States, Japan and Canada. Keyur P. Patel's co-authors include L. Jeffrey Medeiros, Hagop M. Kantarjian, Rajyalakshmi Luthra, Mark J. Routbort, Farhad Ravandi, Jörge E. Cortes, Guillermo Garcia‐Manero, Bedia A. Barkoh, Rashmi Kanagal‐Shamanna and Elias Jabbour and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Keyur P. Patel

316 papers receiving 8.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Keyur P. Patel United States 48 4.0k 2.8k 2.4k 2.0k 2.0k 334 8.6k
Meir Wetzler United States 48 5.0k 1.2× 3.0k 1.1× 2.1k 0.9× 2.1k 1.1× 885 0.5× 245 8.6k
Christian Récher France 49 5.0k 1.2× 4.4k 1.6× 1.8k 0.7× 1.9k 1.0× 712 0.4× 299 9.1k
Rajyalakshmi Luthra United States 65 4.1k 1.0× 5.0k 1.7× 3.6k 1.5× 3.6k 1.8× 3.8k 1.9× 308 13.7k
Pellegrino Musto Italy 52 5.6k 1.4× 4.3k 1.5× 2.4k 1.0× 3.5k 1.8× 731 0.4× 386 9.7k
Claude Preudhomme France 62 9.4k 2.3× 5.7k 2.0× 4.4k 1.8× 2.4k 1.2× 1.4k 0.7× 356 13.3k
Eva Hellström‐Lindberg Sweden 40 8.2k 2.0× 4.0k 1.4× 3.8k 1.6× 1.2k 0.6× 721 0.4× 187 10.6k
Uwe Platzbecker Germany 54 8.8k 2.2× 3.6k 1.3× 4.1k 1.7× 1.7k 0.9× 692 0.4× 543 11.3k
Rami S. Komrokji United States 45 5.5k 1.3× 2.6k 0.9× 3.1k 1.3× 1.2k 0.6× 403 0.2× 584 7.5k
Courtney D. DiNardo United States 53 10.1k 2.5× 6.6k 2.3× 3.3k 1.4× 2.6k 1.3× 1.5k 0.8× 628 13.5k
Robert B. Gerbing United States 51 3.9k 1.0× 4.6k 1.6× 1.3k 0.5× 2.1k 1.1× 2.1k 1.1× 239 11.0k

Countries citing papers authored by Keyur P. Patel

Since Specialization
Citations

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

Fields of papers citing papers by Keyur P. Patel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keyur P. Patel. 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 Keyur P. Patel. The network helps show where Keyur P. Patel may publish in the future.

Co-authorship network of co-authors of Keyur P. Patel

This figure shows the co-authorship network connecting the top 25 collaborators of Keyur P. Patel. A scholar is included among the top collaborators of Keyur P. Patel 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 Keyur P. Patel. Keyur P. Patel 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
1.
Yang, Richard K., Fatima Zahra Jelloul, Rajyalakshmi Luthra, et al.. (2025). Routine Clinical Liquid Biopsy Testing for Solid Tumors Delivers the Promise of Minimally Invasive Detection of Genomic Variants With a Faster Turnaround Time. JCO Precision Oncology. 9(9). e2400299–e2400299. 2 indexed citations
2.
Gouda, Mohamed A., Filip Jankú, Ying Yuan, et al.. (2025). Concordance between Tumor Tissue and Plasma DNA Genotyping in the NCI-MATCH Trial (EAY131). Clinical Cancer Research. 31(20). 4299–4310. 1 indexed citations
4.
Lucas, F. Anthony San, Keyur P. Patel, Wai Chin Foo, et al.. (2024). Circulating tumor DNA as a predictive biomarker for pathologic response after treatment with neoadjuvant immunotherapy for localized dMMR/MSI-H colorectal cancer.. Journal of Clinical Oncology. 42(16_suppl). 3612–3612.
6.
Daniels, Molly S., Ecaterina E. Dumbrava, Ying Yuan, et al.. (2023). Limited Independent Follow-Up with Germline Testing of Variants Detected in BRCA1 and BRCA2 by Tumor-Only Sequencing. SHILAP Revista de lepidopterología. 7(1). 7–17. 1 indexed citations
8.
Senapati, Jayastu, Sanam Loghavi, Nicholas J. Short, et al.. (2023). Venetoclax abrogates the prognostic impact of splicing factor gene mutations in newly diagnosed acute myeloid leukemia. Blood. 142(19). 1647–1657. 35 indexed citations
9.
Jabbour, Elias, Koji Sasaki, Fadi Haddad, et al.. (2023). The outcomes of patients with chronic myeloid leukemia treated with third‐line BCR::ABL1 tyrosine kinase inhibitors. American Journal of Hematology. 98(4). 658–665. 15 indexed citations
10.
Senapati, Jayastu, Mahran Shoukier, Guillermo Garcia‐Manero, et al.. (2022). Activity of decitabine as maintenance therapy in core binding factor acute myeloid leukemia. American Journal of Hematology. 97(5). 574–582. 15 indexed citations
12.
Sasaki, Koji, Farhad Ravandi, Tapan M. Kadia, et al.. (2022). Prediction of survival with intensive chemotherapy in acute myeloid leukemia. American Journal of Hematology. 97(7). 865–876. 13 indexed citations
13.
Chifotides, Helen T., Lucia Masárová, Mansour Alfayez, et al.. (2020). Outcome of patients with IDH1/2-mutated post–myeloproliferative neoplasm AML in the era of IDH inhibitors. Blood Advances. 4(21). 5336–5342. 37 indexed citations
14.
Lachowiez, Curtis A., Sarah A. Bannon, Sanam Loghavi, et al.. (2020). Clonal evolution and treatment outcomes in hematopoietic neoplasms arising in patients with germline RUNX1 mutations. American Journal of Hematology. 95(11). E313–E315. 3 indexed citations
15.
Quesada, Andres, Mark J. Routbort, Courtney D. DiNardo, et al.. (2019). DDX41 mutations in myeloid neoplasms are associated with male gender, TP53 mutations and high‐risk disease. American Journal of Hematology. 94(7). 757–766. 71 indexed citations
16.
Sasaki, Koji, Hagop M. Kantarjian, Tapan M. Kadia, et al.. (2019). Sorafenib plus intensive chemotherapy improves survival in patients with newly diagnosed, FLT3‐internal tandem duplication mutation–positive acute myeloid leukemia. Cancer. 125(21). 3755–3766. 36 indexed citations
17.
Chen, Hui, Rajyalakshmi Luthra, Mark J. Routbort, et al.. (2018). Molecular Profile of Advanced Thyroid Carcinomas by Next-Generation Sequencing: Characterizing Tumors Beyond Diagnosis for Targeted Therapy. Molecular Cancer Therapeutics. 17(7). 1575–1584. 70 indexed citations
18.
Ishizawa, Jo, Kenji Nakamaru, Takahiko Seki, et al.. (2018). Predictive Gene Signatures Determine Tumor Sensitivity to MDM2 Inhibition. Cancer Research. 78(10). 2721–2731. 44 indexed citations
19.
Estrella, Jeannelyn S., Michael T. Tetzlaff, Roland L. Bassett, et al.. (2015). Assessment of BRAF V600E Status in Colorectal Carcinoma: Tissue-Specific Discordances between Immunohistochemistry and Sequencing. Molecular Cancer Therapeutics. 14(12). 2887–2895. 33 indexed citations
20.
Goswami, Rashmi S., Keyur P. Patel, Rajesh R. Singh, et al.. (2015). Hotspot Mutation Panel Testing Reveals Clonal Evolution in a Study of 265 Paired Primary and Metastatic Tumors. Clinical Cancer Research. 21(11). 2644–2651. 59 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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