Lee‐Yung Shih

12.2k total citations
195 papers, 3.6k citations indexed

About

Lee‐Yung Shih is a scholar working on Hematology, Genetics and Molecular Biology. According to data from OpenAlex, Lee‐Yung Shih has authored 195 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 116 papers in Hematology, 71 papers in Genetics and 52 papers in Molecular Biology. Recurrent topics in Lee‐Yung Shih's work include Acute Myeloid Leukemia Research (74 papers), Chronic Myeloid Leukemia Treatments (51 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (40 papers). Lee‐Yung Shih is often cited by papers focused on Acute Myeloid Leukemia Research (74 papers), Chronic Myeloid Leukemia Treatments (51 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (40 papers). Lee‐Yung Shih collaborates with scholars based in Taiwan, United States and Japan. Lee‐Yung Shih's co-authors include Tseng‐tong Kuo, Ming‐Chung Kuo, Po Dunn, Po‐Nan Wang, Jin‐Hou Wu, Der‐Cherng Liang, Tung‐Liang Lin, Heng‐Leong Chan, Der-Cherng Liang and Hsi‐Che Liu and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Lee‐Yung Shih

186 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lee‐Yung Shih Taiwan 30 1.7k 1.2k 776 663 661 195 3.6k
Ilse Schwarzinger Austria 36 1.8k 1.0× 1.2k 1.0× 914 1.2× 840 1.3× 437 0.7× 136 4.0k
Daniela Damiani Italy 31 1.2k 0.7× 843 0.7× 565 0.7× 1.1k 1.7× 381 0.6× 134 3.0k
Dina Ben‐Yehuda Israel 35 1.7k 1.0× 2.1k 1.7× 1.2k 1.5× 1.3k 2.0× 1.4k 2.1× 124 4.8k
Meinolf Suttorp Germany 32 2.6k 1.5× 513 0.4× 1.2k 1.5× 944 1.4× 287 0.4× 184 4.0k
G. Verhoef Belgium 35 1.7k 1.0× 951 0.8× 1.1k 1.4× 1.5k 2.2× 1.4k 2.1× 103 4.4k
Hirokazu Murakami Japan 26 1.3k 0.8× 885 0.7× 478 0.6× 475 0.7× 530 0.8× 204 2.6k
Donna L. Forrest Canada 27 1.4k 0.8× 422 0.4× 737 0.9× 482 0.7× 392 0.6× 110 2.3k
Chihiro Shimazaki Japan 33 2.4k 1.4× 1.5k 1.2× 813 1.0× 1.2k 1.8× 594 0.9× 213 4.0k
Suresh H. Advani India 25 708 0.4× 578 0.5× 462 0.6× 1.1k 1.6× 560 0.8× 250 3.0k
Philippe Casassus France 30 3.3k 1.9× 2.3k 2.0× 773 1.0× 2.0k 3.0× 604 0.9× 80 6.1k

Countries citing papers authored by Lee‐Yung Shih

Since Specialization
Citations

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

Fields of papers citing papers by Lee‐Yung Shih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lee‐Yung Shih. 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 Lee‐Yung Shih. The network helps show where Lee‐Yung Shih may publish in the future.

Co-authorship network of co-authors of Lee‐Yung Shih

This figure shows the co-authorship network connecting the top 25 collaborators of Lee‐Yung Shih. A scholar is included among the top collaborators of Lee‐Yung Shih 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 Lee‐Yung Shih. Lee‐Yung Shih 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
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Chang, Hung, Ming‐Chung Kuo, Jin‐Hou Wu, et al.. (2025). Genetic evolution of myeloproliferative neoplasms from chronic phase to blastic phase: An analysis of 46 paired samples. Cancer. 131(16). e70048–e70048.
3.
Lin, Tung‐Liang, Yu‐Shin Hung, Hung Chang, et al.. (2025). Prognostic impact of pre-treatment and post-treatment plasma Epstein-Barr virus DNA in peripheral T-cell lymphomas. Annals of Medicine. 57(1). 2478315–2478315.
4.
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Chuang, Wen‐Yu, Hung Chang, Lee‐Yung Shih, et al.. (2024). Identification of CD5/SOX11 double-negative pleomorphic mantle cell lymphoma. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 485(2). 323–334. 1 indexed citations
6.
Mallo, Mar, Heinz Tuechler, Leonor Arenillas, et al.. (2023). Regions of homozygosity confer a worse prognostic impact in myelodysplastic syndrome with normal karyotype. SHILAP Revista de lepidopterología. 4(2). 446–449. 3 indexed citations
7.
Chuang, Wen‐Yu, Wei-Hsiang Yu, Hung Chang, et al.. (2022). Deep Learning–Based Nuclear Morphometry Reveals an Independent Prognostic Factor in Mantle Cell Lymphoma. American Journal Of Pathology. 192(12). 1763–1778. 3 indexed citations
8.
Ochi, Yotaro, Kenichi Yoshida, Ying‐Jung Huang, et al.. (2018). Molecular Profiling of Blastic Transformation in Chronic Myeloid Leukemia. Blood. 132(Supplement 1). 1725–1725. 3 indexed citations
9.
Hughes, Timothy P., Alaa Elhaddad, Jake Shortt, et al.. (2017). Nilotinib dose‐optimization in newly diagnosed chronic myeloid leukaemia in chronic phase: final results from ENESTxtnd. British Journal of Haematology. 179(2). 219–228. 16 indexed citations
10.
Chang, Tsung‐Yen, Jin‐Yao Lai, Tang‐Her Jaing, et al.. (2017). Development of a gastric carcinoid tumor following allogeneic hematopoietic stem cell transplantation for early T‐cell precursor acute lymphoblastic leukemia. Pediatric Transplantation. 21(4). 1 indexed citations
11.
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Shih, Lee‐Yung, et al.. (2017). A case of nilotinib-induced keratosis pilaris-like perifollicular fibrosis with a brief review of the literature. Dermatologica Sinica. 35(3). 163–165. 2 indexed citations
13.
Kuo, Ming‐Chung, Chien‐Feng Sun, Jin‐Hou Wu, et al.. (2017). The clinical and prognostic relevance of driver mutations in 203 Taiwanese patients with primary myelofibrosis. Journal of Clinical Pathology. 71(6). 514–521. 3 indexed citations
14.
Tsai, Shu‐Chun, Lee‐Yung Shih, Sung‐Tzu Liang, et al.. (2015). Biological Activities of RUNX1 Mutants Predict Secondary Acute Leukemia Transformation from Chronic Myelomonocytic Leukemia and Myelodysplastic Syndromes. Clinical Cancer Research. 21(15). 3541–3551. 41 indexed citations
15.
Shih, Lee‐Yung, Hung Chang, Po‐Nan Wang, et al.. (2013). Clinical Features of Testicular Lymphoma. Acta Haematologica. 131(3). 187–192. 1 indexed citations
16.
Lin, Yu‐Sheng, Pao‐Hsien Chu, Ming‐Chung Kuo, et al.. (2006). Use of a B-Type Natriuretic Peptide in Evaluating the Treatment Response of a Relapsed Lymphoma with Cardiac Involvement. International Journal of Hematology. 83(1). 44–46. 3 indexed citations
17.
Dunn, Po, Tseng‐tong Kuo, Lee‐Yung Shih, et al.. (2004). Primary Salivary Gland Lymphoma: A Clinicopathologic Study of 23 Cases in Taiwan. Acta Haematologica. 112(4). 203–208. 38 indexed citations
18.
Chang, Hsiu‐Hao, Lee‐Yung Shih, & T T Kuo. (2003). Primary aleukemic myeloid leukemia cutis treated successfully with combination chemotherapy: report of a case and review of the literature. Annals of Hematology. 82(7). 435–439. 13 indexed citations
19.
Shih, Lee‐Yung. (1986). Identification of monocytic nature in acute undifferentiated leukemia by in vitro marrow culture study. Annals of Hematology. 52(5). 323–326. 1 indexed citations
20.
Shih, Lee‐Yung, et al.. (1985). Marrow culture studies in adult acute myeloid leukemia at diagnosis and during complete remission. Annals of Hematology. 50(4). 225–232. 6 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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