Chung-Che Chang

1.4k total citations
49 papers, 1.0k citations indexed

About

Chung-Che Chang is a scholar working on Oncology, Pathology and Forensic Medicine and Molecular Biology. According to data from OpenAlex, Chung-Che Chang has authored 49 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Oncology, 15 papers in Pathology and Forensic Medicine and 14 papers in Molecular Biology. Recurrent topics in Chung-Che Chang's work include Lymphoma Diagnosis and Treatment (12 papers), Acute Myeloid Leukemia Research (10 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (8 papers). Chung-Che Chang is often cited by papers focused on Lymphoma Diagnosis and Treatment (12 papers), Acute Myeloid Leukemia Research (10 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (8 papers). Chung-Che Chang collaborates with scholars based in United States, Taiwan and China. Chung-Che Chang's co-authors include Jianguo Wen, Kirtee Raparia, Tarek Mekhail, Patricia Chévez‐Barrios, Jian Guan, Yongdong Feng, Arsalan Ahmed, Youli Zu, Barbara A. Bresnahan and Eric P. Cohen and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Chung-Che Chang

49 papers receiving 990 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chung-Che Chang United States 18 529 255 236 231 159 49 1.0k
Jeong Hee Cho‐Vega United States 18 581 1.1× 476 1.9× 156 0.7× 512 2.2× 181 1.1× 44 1.4k
Yuji Yufu Japan 14 379 0.7× 384 1.5× 238 1.0× 244 1.1× 137 0.9× 36 872
DL Longo United States 18 400 0.8× 323 1.3× 603 2.6× 256 1.1× 233 1.5× 31 1.2k
Noriko Fukuhara Japan 21 390 0.7× 530 2.1× 304 1.3× 424 1.8× 459 2.9× 152 1.5k
Masaaki Noguchi Japan 14 180 0.3× 261 1.0× 163 0.7× 245 1.1× 181 1.1× 85 866
Gigliola Reato Italy 18 542 1.0× 298 1.2× 262 1.1× 484 2.1× 278 1.7× 36 1.4k
Ayse U. Akarca United Kingdom 14 475 0.9× 196 0.8× 253 1.1× 183 0.8× 44 0.3× 34 773
Christian Kneitz Germany 17 206 0.4× 216 0.8× 585 2.5× 184 0.8× 215 1.4× 29 1.1k
Upendra P. Hegde United States 16 578 1.1× 438 1.7× 272 1.2× 247 1.1× 375 2.4× 49 1.3k
Paul Drillenburg Netherlands 20 442 0.8× 350 1.4× 313 1.3× 374 1.6× 94 0.6× 37 1.4k

Countries citing papers authored by Chung-Che Chang

Since Specialization
Citations

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

Fields of papers citing papers by Chung-Che Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chung-Che Chang. 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 Chung-Che Chang. The network helps show where Chung-Che Chang may publish in the future.

Co-authorship network of co-authors of Chung-Che Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Chung-Che Chang. A scholar is included among the top collaborators of Chung-Che Chang 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 Chung-Che Chang. Chung-Che Chang 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.
Ji, Yuan, Jun Wang, Qi Shen, et al.. (2022). Mast cell sarcoma: clinicopathologic and molecular analysis of 10 new cases and review of literature. Modern Pathology. 35(7). 865–874. 7 indexed citations
2.
Wang, Ren‐Ching, et al.. (2022). Clinicopathologic Features of Lymphoproliferative Neoplasms Involving the Liver. Medicina. 58(1). 72–72. 1 indexed citations
3.
Vasalos, Patricia, Chung-Che Chang, Jason N. Rosenbaum, et al.. (2022). Getting Your Laboratory on Track With Neurotrophic Receptor Tyrosine Kinase. Archives of Pathology & Laboratory Medicine. 147(8). 872–884. 2 indexed citations
4.
6.
Tao, Luwei, Ruoyu Miao, Tarek Mekhail, et al.. (2020). Prognostic Value of KRAS Mutation Subtypes and PD-L1 Expression in Patients With Lung Adenocarcinoma. Clinical Lung Cancer. 22(4). e506–e511. 17 indexed citations
7.
Wang, Ren‐Ching, Luwei Tao, Akriti Jain, et al.. (2019). Prognostic Significance of the Dynamic Change of Programmed Death-ligand 1 Expression in Patients with Multiple Myeloma. Cureus. 11(4). e4401–e4401. 7 indexed citations
8.
Tran, Tien Anh N., et al.. (2019). Superficial and Deep Cutaneous Involvement by RAS-Associated Autoimmunne Leukoproliferative Disease (RALD Cutis): A Histologic Mimicker of Histiocytoid Sweet Syndrome. American Journal of Dermatopathology. 41(8). 606–610. 3 indexed citations
9.
Guan, Jian, et al.. (2017). Programmed Death Ligand-1 (PD-L1) Expression in the Programmed Death Receptor-1 (PD-1)/PD-L1 Blockade: A Key Player Against Various Cancers. Archives of Pathology & Laboratory Medicine. 141(6). 851–861. 93 indexed citations
11.
Hussain, Faraz, Damla Turgut, Narsingh Deo, et al.. (2017). A theorem proving approach for automatically synthesizing visualizations of flow cytometry data. BMC Bioinformatics. 18(S8). 245–245. 1 indexed citations
12.
Ko, Bor‐Sheng, Tzu-Ching Chang, Chien‐Hung Chen, et al.. (2009). Bortezomib suppresses focal adhesion kinase expression via interrupting nuclear factor-kappa B. Life Sciences. 86(5-6). 199–206. 31 indexed citations
13.
Chuang, Shih‐Sung, et al.. (2009). Chronic lymphocytic leukemia with paraimmunoblastic transformation – with comparative genomic hybridization and review of the literature. Pathology - Research and Practice. 206(4). 276–281. 2 indexed citations
14.
Wen, Jianguo, Yongdong Feng, Wan‐Ting Huang, et al.. (2009). Phenotyping Studies of Clonotypic B Lymphocytes From Patients With Multiple Myeloma by Flow Cytometry. Archives of Pathology & Laboratory Medicine. 133(10). 1594–1599. 9 indexed citations
15.
Raparia, Kirtee, Chung-Che Chang, & Patricia Chévez‐Barrios. (2009). Intraocular lymphoma: diagnostic approach and immunophenotypic findings in vitrectomy specimens.. PubMed. 133(8). 1233–7. 40 indexed citations
16.
Bollard, Catherine M., Stephen Gottschalk, Ann M. Leen, et al.. (2007). Complete responses of relapsed lymphoma following genetic modification of tumor-antigen presenting cells and T-lymphocyte transfer. Blood. 110(8). 2838–2845. 213 indexed citations
17.
Chang, Chung-Che. (2006). BCR/ABL-negative chronic myeloproliferative disorders: JAK2 mutation and beyond.. Archives of Pathology & Laboratory Medicine. 130(8). 1123–5. 3 indexed citations
18.
Mody, Dina R., et al.. (2005). Restricted / Light Chain Ratio by Flow Cytometry in Germinal Center B Cells in Hashimoto Thyroiditis. American Journal of Clinical Pathology. 125(1). 42–48. 1 indexed citations
19.
Chang, Chung-Che, et al.. (2003). Follicular Hyperplasia, Follicular Lysis, and Progressive Transformation of Germinal Centers: A Sequential Spectrum of Morphologic Evolution in Lymphoid Hyperplasia. American Journal of Clinical Pathology. 120(3). 322–326. 28 indexed citations
20.
Cohen, Eric P., et al.. (2001). POLYOMA VIRUS INFECTION AFTER RENAL TRANSPLANTATION1. Transplantation. 71(7). 896–899. 106 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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