Jun Horiguchi

11.0k total citations
383 papers, 7.2k citations indexed

About

Jun Horiguchi is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Cancer Research. According to data from OpenAlex, Jun Horiguchi has authored 383 papers receiving a total of 7.2k indexed citations (citations by other indexed papers that have themselves been cited), including 101 papers in Oncology, 67 papers in Radiology, Nuclear Medicine and Imaging and 65 papers in Cancer Research. Recurrent topics in Jun Horiguchi's work include Breast Cancer Treatment Studies (47 papers), HER2/EGFR in Cancer Research (34 papers) and Cardiac Imaging and Diagnostics (33 papers). Jun Horiguchi is often cited by papers focused on Breast Cancer Treatment Studies (47 papers), HER2/EGFR in Cancer Research (34 papers) and Cardiac Imaging and Diagnostics (33 papers). Jun Horiguchi collaborates with scholars based in Japan, United Kingdom and United States. Jun Horiguchi's co-authors include Tsuyoshi Miyaoka, Katsuhide Ito, Tetsunari Oyama, Takuji Inagaki, Hideya Yamamoto, Toshiro Kitagawa, Soichi Mizuno, Yasushi Inami, Hideaki YASUDA and Sasagu Kurozumi 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

Jun Horiguchi

360 papers receiving 7.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Horiguchi Japan 42 1.6k 1.4k 1.2k 1.0k 990 383 7.2k
Massimiliano Copetti Italy 54 1.4k 0.9× 2.0k 1.4× 512 0.4× 675 0.7× 692 0.7× 309 9.5k
Mark Lubberink Sweden 50 4.3k 2.7× 1.5k 1.1× 1.7k 1.5× 317 0.3× 646 0.7× 291 8.7k
Peter J. Ell United Kingdom 42 1.9k 1.2× 436 0.3× 675 0.6× 1.2k 1.2× 1.3k 1.4× 156 6.2k
Axel Montagne United States 35 1.1k 0.7× 2.2k 1.5× 446 0.4× 415 0.4× 226 0.2× 66 9.4k
Osama Sabri Germany 57 3.7k 2.3× 1.6k 1.1× 506 0.4× 301 0.3× 772 0.8× 432 11.2k
Isabelle M. Germano United States 44 602 0.4× 2.7k 1.9× 660 0.6× 579 0.6× 656 0.7× 163 8.0k
Thera P. Links Netherlands 53 638 0.4× 1.6k 1.2× 1.4k 1.2× 974 1.0× 2.2k 2.3× 277 10.4k
Melanie D. Sweeney United States 20 846 0.5× 2.5k 1.8× 499 0.4× 334 0.3× 217 0.2× 23 9.7k
Merja Haaparanta‐Solin Finland 53 2.1k 1.3× 1.4k 1.0× 245 0.2× 380 0.4× 526 0.5× 191 8.0k
Sang Kun Lee South Korea 56 811 0.5× 2.7k 1.9× 586 0.5× 1.2k 1.1× 409 0.4× 364 11.4k

Countries citing papers authored by Jun Horiguchi

Since Specialization
Citations

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

Fields of papers citing papers by Jun Horiguchi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Horiguchi

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Horiguchi. A scholar is included among the top collaborators of Jun Horiguchi 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 Jun Horiguchi. Jun Horiguchi 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.
Katayama, Ayaka, et al.. (2024). Current status and prospects of artificial intelligence in breast cancer pathology: convolutional neural networks to prospective Vision Transformers. International Journal of Clinical Oncology. 29(11). 1648–1668. 7 indexed citations
2.
Kurozumi, Sasagu, Naohiko Seki, Chikako Honda, et al.. (2023). Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer. International Journal of Molecular Sciences. 25(1). 35–35. 3 indexed citations
3.
Fujii, Takaaki, et al.. (2020). Phase II study of sequential S-1 and cyclophosphamide therapy in patients with metastatic breast cancer. BMC Cancer. 20(1). 1068–1068. 2 indexed citations
4.
Kurozumi, Sasagu, Kenichi Inoue, Hiroshi Matsumoto, et al.. (2019). Clinicopathological values of PD-L1 expression in HER2-positive breast cancer. Scientific Reports. 9(1). 16662–16662. 39 indexed citations
5.
Noguchi, Emi, Kenji Tamura, Masaya Hattori, et al.. (2018). Trastuzumab emtansine plus pertuzumab in Japanese patients with HER2-positive metastatic breast cancer: a phase Ib study. Breast Cancer. 26(1). 39–46. 1 indexed citations
6.
Kurozumi, Sasagu, Yuri Yamaguchi, Hiroshi Matsumoto, et al.. (2018). Comparing protein and mRNA expressions of the human epidermal growth factor receptor family in estrogen receptor-positive breast cancer. Medical Molecular Morphology. 52(2). 90–98. 5 indexed citations
7.
Katayama, Ayaka, et al.. (2017). Expression patterns of claudins in patients with triple‐negative breast cancer are associated with nodal metastasis and worse outcome. Pathology International. 67(8). 404–413. 25 indexed citations
8.
Ogawa, Yoshiyuki, Shinji Kunishima, Yuri Uchiyama, et al.. (2016). Successful management of perioperative hemostasis in a patient with Glanzmann thrombasthenia who underwent a right total mastectomy. International Journal of Hematology. 105(2). 221–225. 1 indexed citations
9.
Kurozumi, Sasagu, Yuri Yamaguchi, Shinichi Hayashi, et al.. (2016). Prognostic value of the ubiquitin ligase carboxyl terminus of the Hsc70‐interacting protein in postmenopausal breast cancer. Cancer Medicine. 5(8). 1873–1882. 12 indexed citations
10.
11.
Horiguchi, Jun, et al.. (2013). Juvenile fibroadenoma in a 13-year-old female. Nihon Rinsho Geka Gakkai Zasshi (Journal of Japan Surgical Association). 74(3). 640–644.
12.
Inagaki, Takuji, Masa Ieda, Satoko Yamashita, Tsuyoshi Miyaoka, & Jun Horiguchi. (2011). Salivary Alpha-Amylase Reactivity under Psycho-Physiological Stress. A Nonverbal Communication Measurement Tool?. Journal of Behavioral and Brain Science. 1(1). 12–15. 8 indexed citations
13.
Horiguchi, Jun, Tetsunari Oyama, Daisuke Takata, et al.. (2011). Pathological complete response and prognosis in patients receiving neoadjuvant paclitaxel and trastuzumab with and without anthracyclines for stage II and III, HER2-positive operable breast cancer: a single-institute experience.. PubMed. 31(9). 3041–6. 7 indexed citations
14.
Ishikawa, Yuko, Jun Horiguchi, Hiroki Nakajima, et al.. (2011). Triple‐negative breast cancer: Histological subtypes and immunohistochemical and clinicopathological features. Cancer Science. 102(3). 656–662. 24 indexed citations
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Horiguchi, Jun, Tetsunari Oyama, Yukio Koibuchi, et al.. (2009). Neoadjuvant weekly paclitaxel with and without trastuzumab in locally advanced or metastatic breast cancer.. PubMed. 29(2). 517–24. 14 indexed citations
18.
Takai, Yoshiki, Yuichi Iino, & Jun Horiguchi. (2009). A Study of 41 Cases of Mondor's Disease. The Kitakanto Medical Journal. 59(3). 255–258. 1 indexed citations
19.
Horiguchi, Jun, Noriaki Matsuura, Hideya Yamamoto, et al.. (2009). Evaluation of Attenuation-Based Tube Current Control in Coronary Artery Calcium Scoring on Prospective ECG-triggered 64-detector CT. Academic Radiology. 16(10). 1231–1240. 7 indexed citations
20.
Iino, Yuichi, Michio Maemura, Hajime Takei, et al.. (1996). Breast conserving surgery with nipple resection.. PubMed. 16(5B). 3185–7. 5 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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