Gen Iinuma

970 total citations
42 papers, 692 citations indexed

About

Gen Iinuma is a scholar working on Oncology, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Gen Iinuma has authored 42 papers receiving a total of 692 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Oncology, 18 papers in Surgery and 16 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Gen Iinuma's work include Colorectal Cancer Screening and Detection (17 papers), Colorectal Cancer Surgical Treatments (12 papers) and Radiomics and Machine Learning in Medical Imaging (10 papers). Gen Iinuma is often cited by papers focused on Colorectal Cancer Screening and Detection (17 papers), Colorectal Cancer Surgical Treatments (12 papers) and Radiomics and Machine Learning in Medical Imaging (10 papers). Gen Iinuma collaborates with scholars based in Japan, United States and United Kingdom. Gen Iinuma's co-authors include Takayuki Akasu, Noriyuki Moriyama, Yukio Muramatsu, Yutaka Saito, Hiroyuki Tsuda, Takahiro Kozu, Masaaki Iigo, Tadao Kakizoe, David B. Alexander and Yasuo Ohashi and has published in prestigious journals such as Journal of Clinical Oncology, Radiology and International Journal of Molecular Sciences.

In The Last Decade

Gen Iinuma

41 papers receiving 668 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gen Iinuma Japan 13 304 258 182 157 130 42 692
Kazutake Okada Japan 17 492 1.6× 385 1.5× 180 1.0× 52 0.3× 74 0.6× 74 828
Jona Stadler Israel 13 249 0.8× 155 0.6× 91 0.5× 78 0.5× 37 0.3× 25 707
Ignacio Herrero Spain 13 326 1.1× 250 1.0× 120 0.7× 42 0.3× 82 0.6× 25 1.2k
Qingbin Wu China 19 521 1.7× 350 1.4× 200 1.1× 75 0.5× 12 0.1× 64 897
Eugenio Ciancia Italy 12 125 0.4× 152 0.6× 117 0.6× 26 0.2× 53 0.4× 39 609
Ramin Schirin-Sokhan Germany 12 259 0.9× 247 1.0× 203 1.1× 74 0.5× 16 0.1× 15 660
B Boozari Germany 12 92 0.3× 148 0.6× 77 0.4× 105 0.7× 21 0.2× 36 550
Silvano Andorno Italy 17 147 0.5× 136 0.5× 127 0.7× 15 0.1× 49 0.4× 30 556
Francisco Navarro Spain 11 327 1.1× 318 1.2× 112 0.6× 18 0.1× 22 0.2× 25 795
Tatsuyuki Osuga Japan 16 65 0.2× 142 0.6× 260 1.4× 248 1.6× 14 0.1× 66 711

Countries citing papers authored by Gen Iinuma

Since Specialization
Citations

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

Fields of papers citing papers by Gen Iinuma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gen Iinuma

This figure shows the co-authorship network connecting the top 25 collaborators of Gen Iinuma. A scholar is included among the top collaborators of Gen Iinuma 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 Gen Iinuma. Gen Iinuma 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.
Kawata, Yoshiki, et al.. (2019). Metastatic lymph node analysis of colorectal cancer using quadruple-phase CT images. 138–138. 1 indexed citations
2.
Shida, Dai, Gen Iinuma, Shunsuke Tsukamoto, et al.. (2019). Preoperative T staging of colon cancer using CT colonography with multiplanar reconstruction: new diagnostic criteria based on “bordering vessels”. International Journal of Colorectal Disease. 34(4). 641–648. 13 indexed citations
3.
4.
Shida, Dai, Gen Iinuma, Hiroki Ochiai, et al.. (2017). Preoperative T staging using CT colonography with multiplanar reconstruction for very low rectal cancer. BMC Cancer. 17(1). 764–764. 13 indexed citations
5.
Igarashi, Ataru, et al.. (2014). Cost-Effectiveness Analysis of CT Colonography for Colorectal Cancer Screening Program to Working Age in Japan. Value in Health Regional Issues. 3. 182–189. 3 indexed citations
6.
Miyake, Mototaka, Gen Iinuma, Stuart A. Taylor, et al.. (2013). Comparative performance of a primary-reader and second-reader paradigm of computer-aided detection for CT colonography in a low-prevalence screening population. Japanese Journal of Radiology. 31(5). 310–319. 8 indexed citations
7.
Iinuma, Gen, et al.. (2011). [Recent progress and future view in diagnostic imaging for colorectal cancer].. PubMed. 69 Suppl 3. 7–15. 1 indexed citations
8.
Tsuda, Hiroyuki, Takahiro Kozu, Gen Iinuma, et al.. (2010). Cancer prevention by bovine lactoferrin: from animal studies to human trial. BioMetals. 23(3). 399–409. 87 indexed citations
9.
Kozu, Takahiro, Gen Iinuma, Yasuo Ohashi, et al.. (2009). Effect of Orally Administered Bovine Lactoferrin on the Growth of Adenomatous Colorectal Polyps in a Randomized, Placebo-Controlled Clinical Trial. Cancer Prevention Research. 2(11). 975–983. 98 indexed citations
10.
Iinuma, Gen, Mototaka Miyake, Yasuaki Arai, et al.. (2009). CT colonography - towards applications for colorectal cancer screening.. PubMed. 9(4). 833–40. 3 indexed citations
11.
Akasu, Takayuki, Gen Iinuma, Masashi Takawa, et al.. (2009). Accuracy of High-Resolution Magnetic Resonance Imaging in Preoperative Staging of Rectal Cancer. Annals of Surgical Oncology. 16(10). 2787–2794. 91 indexed citations
12.
Taylor, Stuart A., Gen Iinuma, Yutaka Saito, Jie Zhang, & Steve Halligan. (2008). CT colonography: computer-aided detection of morphologically flat T1 colonic carcinoma. European Radiology. 18(8). 1666–1673. 25 indexed citations
13.
Morimoto, Tsuyoshi, Gen Iinuma, Junji Shiraishi, et al.. (2008). Computer-aided detection in computed tomography colonography: current status and problems with detection of early colorectal cancer. Radiation Medicine. 26(5). 261–269. 7 indexed citations
14.
Yamamoto, Shuji, et al.. (2007). Technical Aspects of X-ray Micro-computed Tomography: Initial Experience of 27-.MU.m Resolution Using Feldkamp Cone-beam Reconstruction. Japanese Journal of Radiological Technology. 63(2). 257–260. 2 indexed citations
15.
Iinuma, Gen, N. Moriyama, Kunihisa Miyakawa, et al.. (2003). Early invasive colorectal carcinomas with submucosal invasion: radiographic characteristics with barium double contrast images. Abdominal Radiology. 28(4). 492–504. 3 indexed citations
16.
17.
Ishikawa, Tsutomu, Kunihisa Miyakawa, Gen Iinuma, et al.. (1997). Abdominal actinomycosis: Barium enema and computed tomography findings. Journal of Gastroenterology. 32(1). 89–94. 13 indexed citations
18.
Kanematsu, Manabu, et al.. (1992). Rupture of hepatocellular carcinoma: predictive value of CT findings.. American Journal of Roentgenology. 158(6). 1247–1250. 43 indexed citations
19.
Imaeda, T, Yasuhiro Sone, Gen Iinuma, et al.. (1991). Gallium-67 citrate scintigraphy in the pre-operative evaluation of soft tissue tumors of the extremities. Annals of Nuclear Medicine. 5(4). 127–132. 2 indexed citations
20.
Imaeda, T, et al.. (1990). A case of intermittent bleeding Meckel’s diverticulum. Annals of Nuclear Medicine. 4(3). 107–110. 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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