Daichi Kitaguchi

1.3k total citations
71 papers, 747 citations indexed

About

Daichi Kitaguchi is a scholar working on Surgery, Oncology and Biomedical Engineering. According to data from OpenAlex, Daichi Kitaguchi has authored 71 papers receiving a total of 747 indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Surgery, 41 papers in Oncology and 18 papers in Biomedical Engineering. Recurrent topics in Daichi Kitaguchi's work include Colorectal Cancer Surgical Treatments (40 papers), Surgical Simulation and Training (25 papers) and Anorectal Disease Treatments and Outcomes (14 papers). Daichi Kitaguchi is often cited by papers focused on Colorectal Cancer Surgical Treatments (40 papers), Surgical Simulation and Training (25 papers) and Anorectal Disease Treatments and Outcomes (14 papers). Daichi Kitaguchi collaborates with scholars based in Japan, South Korea and United States. Daichi Kitaguchi's co-authors include Masaaki Ito, Nobuyoshi Takeshita, Hiro Hasegawa, Hiroki Matsuzaki, Tatsuya Oda, Masahiko Watanabe, Kensaku Mori, Yuichiro Tsukada, Tsuyoshi Enomoto and Yohei Owada and has published in prestigious journals such as SHILAP Revista de lepidopterología, Annals of Surgery and Scientific Reports.

In The Last Decade

Daichi Kitaguchi

57 papers receiving 734 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daichi Kitaguchi Japan 15 501 316 245 141 110 71 747
Runzhuo Ma United States 14 327 0.7× 62 0.2× 207 0.8× 78 0.6× 127 1.2× 49 570
Hiro Hasegawa Japan 12 335 0.7× 231 0.7× 137 0.6× 84 0.6× 83 0.8× 53 488
Federico Piramide Italy 17 426 0.9× 135 0.4× 199 0.8× 73 0.5× 635 5.8× 102 965
Rutger M. Schols Netherlands 15 435 0.9× 126 0.4× 223 0.9× 100 0.7× 209 1.9× 33 701
Tiago Leal Ghezzi Brazil 6 423 0.8× 265 0.8× 131 0.5× 23 0.2× 161 1.5× 16 590
Pieter De Backer Belgium 11 248 0.5× 42 0.1× 80 0.3× 37 0.3× 180 1.6× 47 408
Francesco Volonté Switzerland 16 574 1.1× 183 0.6× 160 0.7× 41 0.3× 197 1.8× 38 732
Taiga Wakabayashi Japan 15 245 0.5× 165 0.5× 73 0.3× 178 1.3× 138 1.3× 49 632
Jong Keon Jang South Korea 15 181 0.4× 226 0.7× 61 0.2× 253 1.8× 115 1.0× 48 673
G. Volpi Italy 16 237 0.5× 78 0.2× 114 0.5× 41 0.3× 396 3.6× 45 592

Countries citing papers authored by Daichi Kitaguchi

Since Specialization
Citations

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

Fields of papers citing papers by Daichi Kitaguchi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daichi Kitaguchi

This figure shows the co-authorship network connecting the top 25 collaborators of Daichi Kitaguchi. A scholar is included among the top collaborators of Daichi Kitaguchi 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 Daichi Kitaguchi. Daichi Kitaguchi 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.
Kitaguchi, Daichi, et al.. (2025). Automatic surgical skill assessment using a task classification model in laparoscopic sigmoidectomy. Surgical Endoscopy. 39(10). 6423–6429.
2.
Wakabayashi, Masashi, Daichi Kitaguchi, Hiro Hasegawa, et al.. (2025). Identification of Risk Factors in Postoperative Urinary Dysfunction for Rectal Gastrointestinal Stromal Tumors. Annals of Gastroenterological Surgery. 9(6). 1243–1252.
3.
Hasegawa, Hiro, Nobuyoshi Takeshita, Daichi Kitaguchi, et al.. (2025). First-in-human robot-assisted laparoscopic sigmoid resection using ANSUR surgical unit®. Techniques in Coloproctology. 29(1). 142–142.
4.
5.
Kitaguchi, Daichi, Chun Xie, Shinji Hashimoto, et al.. (2024). Free-Viewpoint Video in Open Surgery: Development of Surgical Arena 360. Journal of surgical education. 81(3). 326–329. 1 indexed citations
6.
Kitaguchi, Daichi, et al.. (2024). Deep Learning–Based Real-Time Ureter Identification in Laparoscopic Colorectal Surgery. Diseases of the Colon & Rectum. 67(10). e1596–e1599. 9 indexed citations
7.
Shiraishi, Takuya, Yuji Nishizawa, Hiroomi Ogawa, et al.. (2024). Prospective Multicenter Study to Clarify the Frequency of Peristomal Skin Disorders and Appropriate Evaluation Time in Patients With Malignant Rectal Tumors. Annals of Surgery. 283(4). 687–696.
8.
Kitaguchi, Daichi, et al.. (2024). Automated surgical skill assessment in colorectal surgery using a deep learning-based surgical phase recognition model. Surgical Endoscopy. 38(11). 6347–6355. 4 indexed citations
9.
Kitaguchi, Daichi & Masaaki Ito. (2024). Dissection layer selection based on an understanding of pelvic fascial anatomy in transanal total mesorectal excision. Annals of Coloproctology. 40(4). 375–383.
10.
Kitaguchi, Daichi, et al.. (2024). Deep learning-based surgical step recognition for laparoscopic right-sided colectomy. Langenbeck s Archives of Surgery. 409(1). 309–309. 1 indexed citations
11.
Kitaguchi, Daichi, Hiro Hasegawa, Koji Ikeda, et al.. (2023). Transanal Total Mesorectal Excision for Rectal Cancer: Toward Standardization of the Surgical Technique. SHILAP Revista de lepidopterología. 7(4). 225–231. 3 indexed citations
12.
13.
Komatsu, Masaru, Daichi Kitaguchi, Masahiro Yura, et al.. (2023). Automatic surgical phase recognition-based skill assessment in laparoscopic distal gastrectomy using multicenter videos. Gastric Cancer. 27(1). 187–196. 14 indexed citations
14.
Kojima, Shigehiro, et al.. (2023). Deep-learning-based semantic segmentation of autonomic nerves from laparoscopic images of colorectal surgery: an experimental pilot study. International Journal of Surgery. 109(4). 813–820. 16 indexed citations
15.
Kitaguchi, Daichi, et al.. (2023). Deep learning-based vessel automatic recognition for laparoscopic right hemicolectomy. Surgical Endoscopy. 38(1). 171–178. 11 indexed citations
16.
Kitaguchi, Daichi, Hiro Hasegawa, Koji Ikeda, et al.. (2023). Comparison of postoperative anorectal function between hand-sewn and stapled anastomoses in intersphincteric resection with transanal total mesorectal excision. British journal of surgery. 110(3). 375–376. 2 indexed citations
17.
Kitaguchi, Daichi, Yuichiro Tsukada, Masaaki Ito, et al.. (2023). Survival outcomes following salvage abdominoperineal resection for recurrent and persistent anal squamous cell carcinoma. European Journal of Surgical Oncology. 49(9). 106929–106929. 1 indexed citations
18.
Sakamoto, Shinichi, Daichi Kitaguchi, Nobuyoshi Takeshita, et al.. (2022). Deep Learning-Based Seminal Vesicle and Vas Deferens Recognition in the Posterior Approach of Robot-Assisted Radical Prostatectomy. Urology. 173. 98–103. 5 indexed citations
19.
Kitaguchi, Daichi, Tsuyoshi Enomoto, Yusuke Ohara, et al.. (2020). Laparoscopic surgery for diverticular colovesical fistula: single-center experience of 11 cases. BMC Research Notes. 13(1). 5 indexed citations
20.
Kitaguchi, Daichi, Nobuyoshi Takeshita, Hiroki Matsuzaki, et al.. (2020). Computer-assisted real-time automatic prostate segmentation during TaTME: a single-center feasibility study. Surgical Endoscopy. 35(6). 2493–2499. 32 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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