Teruyuki Ueda

1.0k total citations
21 papers, 830 citations indexed

About

Teruyuki Ueda is a scholar working on Hepatology, Epidemiology and Molecular Biology. According to data from OpenAlex, Teruyuki Ueda has authored 21 papers receiving a total of 830 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Hepatology, 8 papers in Epidemiology and 5 papers in Molecular Biology. Recurrent topics in Teruyuki Ueda's work include Liver Disease Diagnosis and Treatment (6 papers), Hepatitis C virus research (6 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). Teruyuki Ueda is often cited by papers focused on Liver Disease Diagnosis and Treatment (6 papers), Hepatitis C virus research (6 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). Teruyuki Ueda collaborates with scholars based in Japan, United States and South Korea. Teruyuki Ueda's co-authors include Taro Yamashita, Masao Honda, Hajime Takatori, Shuichi Kaneko, Ryuhei Nishino, Yoshio Sakai, Shuichi Kaneko, Katsuhisa Horimoto, Hajime Sunagozaka and Eishiro Mizukoshi and has published in prestigious journals such as Journal of Clinical Oncology, Hepatology and Biochemical and Biophysical Research Communications.

In The Last Decade

Teruyuki Ueda

20 papers receiving 813 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Teruyuki Ueda Japan 10 350 328 286 226 182 21 830
Guobin Wu China 16 448 1.3× 254 0.8× 270 0.9× 249 1.1× 184 1.0× 35 909
Miaojun Han United States 9 225 0.6× 188 0.6× 153 0.5× 305 1.3× 182 1.0× 10 738
Katsuhiko Fujikawa Japan 13 631 1.8× 134 0.4× 189 0.7× 204 0.9× 250 1.4× 20 868
Ruizhao Qi China 11 222 0.6× 192 0.6× 128 0.4× 114 0.5× 325 1.8× 20 706
Shunli Shen China 16 349 1.0× 179 0.5× 249 0.9× 101 0.4× 187 1.0× 32 689
Benjamin Ruf United States 14 280 0.8× 146 0.4× 146 0.5× 192 0.8× 343 1.9× 29 869
Wenying Lu China 16 458 1.3× 141 0.4× 381 1.3× 247 1.1× 152 0.8× 29 885
Zsuzsa Schaff Hungary 18 300 0.9× 160 0.5× 207 0.7× 154 0.7× 181 1.0× 48 820
Catherine A. Lázaro United States 9 293 0.8× 460 1.4× 70 0.2× 201 0.9× 113 0.6× 9 804
Christopher B. McClain United States 6 159 0.5× 295 0.9× 75 0.3× 211 0.9× 175 1.0× 9 670

Countries citing papers authored by Teruyuki Ueda

Since Specialization
Citations

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

Fields of papers citing papers by Teruyuki Ueda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Teruyuki Ueda

This figure shows the co-authorship network connecting the top 25 collaborators of Teruyuki Ueda. A scholar is included among the top collaborators of Teruyuki Ueda 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 Teruyuki Ueda. Teruyuki Ueda 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.
2.
Miyayama, Shiro, Masashi Yamashiro, Rie Ikeda, et al.. (2021). Efficacy of Superselective Conventional Transarterial Chemoembolization Using Guidance Software for Hepatocellular Carcinoma within Three Lesions Smaller Than 3 cm. Cancers. 13(24). 6370–6370. 13 indexed citations
3.
4.
Miyayama, Shiro, Masanori Yoshida, Masashi Yamashiro, et al.. (2019). Outcomes of conventional transarterial chemoembolization for hepatocellular carcinoma ≥10 cm. Hepatology Research. 49(7). 787–798. 19 indexed citations
5.
Notsumata, Kazuo, Yoshimoto Nomura, Akihiro Tanaka, et al.. (2017). High LDL cholesterol in DAA treatment for chronic hepatitis C -Comparative study between each DAA treatment-. Kanzo. 58(4). 255–258. 1 indexed citations
6.
Notsumata, Kazuo, Teruyuki Ueda, Hiroyuki Watanabe, et al.. (2014). Automated risk management of HBV reactivation by encoding patients^|^apos; medical records. Kanzo. 55(2). 91–99. 3 indexed citations
7.
Ueda, Teruyuki, Masao Honda, Katsuhisa Horimoto, et al.. (2013). Gene expression profiling of hepatitis B- and hepatitis C-related hepatocellular carcinoma using graphical Gaussian modeling. Genomics. 101(4). 238–248. 26 indexed citations
8.
Nomura, Yoshimoto, Takashi Kagaya, Teruyuki Ueda, et al.. (2012). The biliary drainage for patients with obstructive jaundice due to hepatocellular carcinoma. Kanzo. 53(11). 734–740. 1 indexed citations
9.
Mizukoshi, Eishiro, Tatsuya Yamashita, Kuniaki Arai, et al.. (2012). Enhancement of tumor-associated antigen-specific T cell responses by radiofrequency ablation of hepatocellular carcinoma. Hepatology. 57(4). 1448–1457. 212 indexed citations
10.
Takeshita, Yumie, Toshinari Takamura, Yuki Kita, et al.. (2012). Beneficial effect of branched-chain amino acid supplementation on glycemic control in chronic hepatitis C patients with insulin resistance: Implications for type 2 diabetes. Metabolism. 61(10). 1388–1394. 30 indexed citations
11.
12.
Ozono, S., Teruyuki Ueda, Hideki Maeda, et al.. (2011). The efficacy and safety of degarelix, a GnRH receptor antagonist: A multicenter, randomized, maintenance dose-finding phase II study with Japanese prostate cancer patients.. Journal of Clinical Oncology. 29(7_suppl). 154–154. 1 indexed citations
13.
Xu, Jing, Yasunori Sato, Kenichi Harada, et al.. (2011). Intraductal papillary neoplasm of the bile duct in liver cirrhosis with hepatocellular carcinoma. World Journal of Gastroenterology. 17(14). 1923–1923. 5 indexed citations
14.
15.
Teramoto, Reiji, Hirotaka Minagawa, Masao Honda, et al.. (2008). Protein expression profile characteristic to hepatocellular carcinoma revealed by 2D-DIGE with supervised learning. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1784(5). 764–772. 42 indexed citations
16.
Honda, Masao, Taro Yamashita, Teruyuki Ueda, et al.. (2008). Differential microRNA expression between hepatitis B and hepatitis C leading disease progression to hepatocellular carcinoma #. Hepatology. 49(4). 1098–1112. 313 indexed citations
17.
Minagawa, Hirotaka, Masao Honda, Kenji Miyazaki, et al.. (2007). Comparative proteomic and transcriptomic profiling of the human hepatocellular carcinoma. Biochemical and Biophysical Research Communications. 366(1). 186–192. 26 indexed citations
18.
Honda, Masao, Taro Yamashita, Teruyuki Ueda, et al.. (2006). Different signaling pathways in the livers of patients with chronic hepatitis B or chronic hepatitis C. Hepatology. 44(5). 1122–1138. 70 indexed citations
19.
Kawai, Yasukazu, R. Kawai, Tomohiro Nakayama, et al.. (1999). Successful treatment of cytomegalovirus retinitis in a patient with malignant lymphoma: a case report and review of the literature.. PubMed. 69(4). 256–9. 8 indexed citations
20.
Sugiyama, Toru, et al.. (1987). [A resected case of hepatocellular carcinoma associated with adenomatous hyperplasia of the liver].. PubMed. 84(6). 1320–4. 1 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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