J. W. Vardiman

4.4k total citations · 2 hit papers
37 papers, 3.2k citations indexed

About

J. W. Vardiman is a scholar working on Genetics, Hematology and Pathology and Forensic Medicine. According to data from OpenAlex, J. W. Vardiman has authored 37 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Genetics, 18 papers in Hematology and 9 papers in Pathology and Forensic Medicine. Recurrent topics in J. W. Vardiman's work include Chronic Lymphocytic Leukemia Research (13 papers), Acute Myeloid Leukemia Research (12 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (9 papers). J. W. Vardiman is often cited by papers focused on Chronic Lymphocytic Leukemia Research (13 papers), Acute Myeloid Leukemia Research (12 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (9 papers). J. W. Vardiman collaborates with scholars based in United States, Germany and United Kingdom. J. W. Vardiman's co-authors include Ayalew Tefferi, Georges Flandrin, Hans Konrad Müller‐Hermelink, Elaine S. Jaffe, J Diébold, Nancy L. Harris, T. Lister, C. D. Bloomfield, HM Golomb and John Anastasi and has published in prestigious journals such as Journal of Clinical Oncology, Blood and JNCI Journal of the National Cancer Institute.

In The Last Decade

J. W. Vardiman

37 papers receiving 3.1k citations

Hit Papers

Classification and diagnosis of myeloproliferative neopla... 1999 2026 2008 2017 2007 1999 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. W. Vardiman United States 20 1.7k 1.2k 1.2k 805 778 37 3.2k
Richard Garand France 32 1.5k 0.9× 1.1k 0.9× 1.5k 1.2× 957 1.2× 917 1.2× 80 3.2k
Stefano Sacchi Italy 30 888 0.5× 1.0k 0.9× 843 0.7× 693 0.9× 999 1.3× 145 2.8k
A. Georgii Germany 30 1.4k 0.8× 616 0.5× 1.3k 1.1× 575 0.7× 516 0.7× 115 2.9k
Diane C. Arthur United States 33 1.1k 0.7× 895 0.7× 2.0k 1.7× 1.0k 1.3× 858 1.1× 78 4.1k
Vito Franco Italy 23 1.2k 0.7× 937 0.8× 727 0.6× 522 0.6× 576 0.7× 70 2.5k
J C Brouet France 28 725 0.4× 553 0.5× 992 0.8× 684 0.8× 626 0.8× 70 2.9k
Juan Luis Garcı́a Spain 29 836 0.5× 806 0.7× 1.2k 1.0× 1.3k 1.6× 984 1.3× 127 3.2k
Bridget S. Wilkins United Kingdom 26 2.5k 1.5× 841 0.7× 1.6k 1.3× 1.6k 2.0× 513 0.7× 81 4.2k
Cesare Guglielmi Italy 24 1.3k 0.7× 2.3k 1.9× 1.4k 1.1× 463 0.6× 1.8k 2.3× 67 3.9k
Yang O. Huh United States 35 1.6k 0.9× 1.3k 1.0× 2.4k 2.0× 664 0.8× 1.2k 1.5× 104 4.7k

Countries citing papers authored by J. W. Vardiman

Since Specialization
Citations

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

Fields of papers citing papers by J. W. Vardiman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. W. Vardiman. 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 J. W. Vardiman. The network helps show where J. W. Vardiman may publish in the future.

Co-authorship network of co-authors of J. W. Vardiman

This figure shows the co-authorship network connecting the top 25 collaborators of J. W. Vardiman. A scholar is included among the top collaborators of J. W. Vardiman 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 J. W. Vardiman. J. W. Vardiman 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.
Cheng, Jason X., John Anastasi, Erica L. Kleinbrink, et al.. (2013). Genome-wide profiling reveals epigenetic inactivation of the PU.1 pathway by histone H3 lysine 27 trimethylation in cytogenetically normal myelodysplastic syndrome. Leukemia. 27(6). 1291–1300. 10 indexed citations
2.
Mesa, Ruben A., Anthony R. Green, Giovanni Barosi, et al.. (2010). MPN-associated myelofibrosis (MPN-MF). Leukemia Research. 35(1). 12–13. 33 indexed citations
3.
Tefferi, Ayalew & J. W. Vardiman. (2007). Classification and diagnosis of myeloproliferative neoplasms: The 2008 World Health Organization criteria and point-of-care diagnostic algorithms. Leukemia. 22(1). 14–22. 669 indexed citations breakdown →
4.
Thiele, J., Hans Michael Kvasnicka, & J. W. Vardiman. (2006). Bone marrow histopathology in the diagnosis of chronic myeloproliferative disorders: A forgotten pearl. Best Practice & Research Clinical Haematology. 19(3). 413–437. 30 indexed citations
5.
Thiele, J., H. M. Kvasnicka, J. W. Vardiman, et al.. (2004). Acute panmyelosis with myelofibrosis: a clinicopathological study on 46 patients including histochemistry of bone marrow biopsies and follow-up. Annals of Hematology. 83(8). 513–21. 12 indexed citations
6.
Byrd, John C., B. Peterson, Lawrence D. Piro, et al.. (2003). A phase II study of cladribine treatment for fludarabine refractory B cell chronic lymphocytic leukemia: results from CALGB Study 9211. Leukemia. 17(2). 323–327. 41 indexed citations
8.
Diebold, Joachim, et al.. (2000). THE WORLD HEALTH ORGANIZATION CLASSIFICATION OF HEMATOLOGICAL MALIGNANCIES REPORT OF THE CLINICAL ADVISORY COMMITTEE MEETING. Journal of Clinical Oncology. 13. 193–207. 167 indexed citations
9.
10.
Harris, Nancy L., Elaine S. Jaffe, J Diébold, et al.. (2000). Lymphoma classification – from controversy to consensus: The R.E.A.L. and WHO Classification of lymphoid neoplasms. Annals of Oncology. 11. S3–S10. 261 indexed citations
11.
Harris, Nancy L., Elaine S. Jaffe, J Diébold, et al.. (1999). The World Health Organization Classification of Neoplastic Diseases of the Hematopoietic and Lymphoid Tissues. Annals of Oncology. 10(12). 1419–1432. 649 indexed citations breakdown →
12.
Anastasi, John, et al.. (1998). Pseudo-Gaucher histiocytes identified up to 1 year after transplantation for CML are BCR/ABL-positive. Leukemia. 12(2). 233–237. 11 indexed citations
13.
Dickstein, Jerome I. & J. W. Vardiman. (1995). Hematopathologic findings in the myeloproliferative disorders.. PubMed. 22(4). 355–73. 46 indexed citations
14.
Hruban, Z., et al.. (1992). Haematopoietic malignancies in zoo animals. Journal of Comparative Pathology. 106(1). 15–24. 42 indexed citations
15.
Golomb, Harvey M., A Fefer, David W. Golde, et al.. (1991). Survival Experience of 195 Patients with Hairy Cell Leukemia Treated in a Multi-Institutional Study with Interferon-Alfa 2B. Leukemia & lymphoma. 4(2). 99–102. 10 indexed citations
16.
Ratain, Mark J., Harvey M. Golomb, J. W. Vardiman, et al.. (1988). Relapse after interferon alfa-2b therapy for hairy-cell leukemia: analysis of prognostic variables.. Journal of Clinical Oncology. 6(11). 1714–1721. 60 indexed citations
17.
Golomb, Harvey M., Mark J. Ratain, A Fefer, et al.. (1988). Randomized Study of the Duration of Treatment With Interferon Alfa-2B in Patients With Hairy Cell Leukemia. JNCI Journal of the National Cancer Institute. 80(5). 369–373. 48 indexed citations
18.
Bitter, MA, et al.. (1988). Hairy-cell leukemia. Morphologic, cytochemical, and immunologic features.. PubMed. 8(1). 179–95. 14 indexed citations
19.
Bitter, MA, et al.. (1988). Hairy-Cell Leukemia. Clinics in Laboratory Medicine. 8(1). 179–195. 8 indexed citations
20.
Check, Irene J., Robert L. Hunter, Theodore Karrison, et al.. (1981). Prognostic significance of immunological tests in lung cancer.. PubMed. 43(2). 362–9. 7 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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