Yuki Shimahara

763 total citations
13 papers, 484 citations indexed

About

Yuki Shimahara is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Yuki Shimahara has authored 13 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Pulmonary and Respiratory Medicine, 6 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Molecular Biology. Recurrent topics in Yuki Shimahara's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Cerebrovascular and Carotid Artery Diseases (4 papers) and Colorectal Cancer Screening and Detection (3 papers). Yuki Shimahara is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Cerebrovascular and Carotid Artery Diseases (4 papers) and Colorectal Cancer Screening and Detection (3 papers). Yuki Shimahara collaborates with scholars based in Japan, United States and Switzerland. Yuki Shimahara's co-authors include Daiju Ueda, Akira Yamamoto, Yukio Miki, Akitoshi Shimazaki, Hideki Nakayama, Kohei Murao, Tomoyuki Noguchi, Changhee Han, Leonardo Rundo and Shin’ichi Satoh and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Yuki Shimahara

12 papers receiving 463 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuki Shimahara Japan 5 223 197 134 105 82 13 484
Mohammad R. Salmanpour Canada 10 254 1.1× 69 0.4× 89 0.7× 136 1.3× 28 0.3× 28 426
Anup Sadhu India 12 209 0.9× 123 0.6× 154 1.1× 23 0.2× 23 0.3× 40 404
Arie Nakhmani United States 12 90 0.4× 210 1.1× 41 0.3× 55 0.5× 28 0.3× 67 517
Clifford Yang United States 11 377 1.7× 85 0.4× 356 2.7× 14 0.1× 63 0.8× 22 673
Bibo Shi United States 10 159 0.7× 80 0.4× 151 1.1× 16 0.2× 30 0.4× 25 375
King Chung Ho United States 8 123 0.6× 101 0.5× 169 1.3× 17 0.2× 22 0.3× 9 354
Keewon Shin South Korea 9 199 0.9× 45 0.2× 122 0.9× 16 0.2× 64 0.8× 21 455
Natascha Claudia D’Amico Italy 7 305 1.4× 73 0.4× 198 1.5× 13 0.1× 25 0.3× 10 538
Avi Ben-Cohen Israel 8 262 1.2× 68 0.3× 209 1.6× 12 0.1× 34 0.4× 10 594
Fangzhou Liao China 8 351 1.6× 306 1.6× 157 1.2× 21 0.2× 9 0.1× 10 599

Countries citing papers authored by Yuki Shimahara

Since Specialization
Citations

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

Fields of papers citing papers by Yuki Shimahara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuki Shimahara

This figure shows the co-authorship network connecting the top 25 collaborators of Yuki Shimahara. A scholar is included among the top collaborators of Yuki Shimahara 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 Yuki Shimahara. Yuki Shimahara is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
2.
3.
Akiyama, Reiko, Takao Goto, Toshiaki Tameshige, et al.. (2023). Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServation. Nature Communications. 14(1). 5792–5792. 4 indexed citations
4.
Ikawa, Fusao, Shigeyuki Sakamoto, Takahito Okazaki, et al.. (2023). Effectiveness of tuning an artificial intelligence algorithm for cerebral aneurysm diagnosis: a study of 10,000 consecutive cases. Scientific Reports. 13(1). 16202–16202. 4 indexed citations
5.
Shimazaki, Akitoshi, Daiju Ueda, Akira Yamamoto, et al.. (2022). Deep learning-based algorithm for lung cancer detection on chest radiographs using the segmentation method. Scientific Reports. 12(1). 727–727. 90 indexed citations
6.
Kamba, Shunsuke, Naoto Tamai, Masakuni Kobayashi, et al.. (2021). Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial. Journal of Gastroenterology. 56(8). 746–757. 77 indexed citations
7.
Kamba, Shunsuke, Sho Takahashi, Masako Nishikawa, et al.. (2021). Detection Accuracy and Latency of Colorectal Lesions with Computer-Aided Detection System Based on Low-Bias Evaluation. Diagnostics. 11(10). 1922–1922. 4 indexed citations
8.
Han, Changhee, Leonardo Rundo, Kohei Murao, et al.. (2021). MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction. BMC Bioinformatics. 22(S2). 31–31. 135 indexed citations
9.
Kamba, Shunsuke, Naoto Tamai, Masakuni Kobayashi, et al.. (2021). ID: 3519580 A MULTICENTRE RANDOMIZED CONTROLLED TRIAL TO VERIFY THE REDUCIBILITY OF ADENOMA MISS RATE OF COLONOSCOPY ASSISTED WITH ARTIFICIAL INTELLIGENCE BASED SOFTWARE. Gastrointestinal Endoscopy. 93(6). AB195–AB195. 2 indexed citations
10.
Shimada, Yuki, Tetsuya Tanimoto, Akihiko Ozaki, et al.. (2020). Incidental cerebral aneurysms detected by a computer-assisted detection system based on artificial intelligence. Medicine. 99(43). e21518–e21518. 14 indexed citations
11.
Shimahara, Yuki, et al.. (2019). IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification. PLoS ONE. 14(2). e0212619–e0212619. 3 indexed citations
12.
Shimahara, Yuki, et al.. (2019). Quantitative Evaluation of Stromule Frequency at Hourly Intervals in <i>Arabidopsis</i> Stomatal Guard Cell Chloroplasts. CYTOLOGIA. 84(1). 31–35. 1 indexed citations
13.
Ueda, Daiju, Akira Yamamoto, Taro Shimono, et al.. (2018). Deep Learning for MR Angiography: Automated Detection of Cerebral Aneurysms. Radiology. 290(1). 187–194. 147 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Mohammad R. Salmanpour Breakdown of academic impact, for papers by Anup Sadhu Breakdown of academic impact, for papers by Arie Nakhmani Breakdown of academic impact, for papers by Clifford Yang Breakdown of academic impact, for papers by Bibo Shi Breakdown of academic impact, for papers by King Chung Ho Breakdown of academic impact, for papers by Keewon Shin Breakdown of academic impact, for papers by Natascha Claudia D’Amico Breakdown of academic impact, for papers by Avi Ben-Cohen Breakdown of academic impact, for papers by Fangzhou Liao
Rankless by CCL
2026