Yukako Yagi

124 papers receiving 3.5k citations

Peers

Yukako Yagi
Comparison fields: 5 of 159
  • Biophysics 781
  • Health Informatics 86
  • Artificial Intelligence 1.7k
  • Radiology, Nuclear Medicine and Imaging 990
  • Computer Vision and Pattern Recognition 572
Replace Darren Treanor with:
Darren Treanor United Kingdom
Nicolas Coudray United States
Gabriele Campanella United States
Mikael Lundin Finland
Narges Razavian United States
Peter Bult Netherlands
Andrew H. Beck United States
Famke Aeffner United States
William D. Wallace United States
Meyke Hermsen Netherlands
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Citations per year

Countries citing papers authored by Yukako Yagi

Since Specialization
Citations

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

Fields of papers citing papers by Yukako Yagi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yukako Yagi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yukako Yagi Line = papers co-authored together Yukako Yagi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 127 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011343
2 2009288
3 2006172
4 2006161
5 2012131
6 2019128
7 2019101
8 201497
9 201195
10 201289
11 200574
12 202173
13 201271
14 201965
15 202159
16 201156
17 201354
18 201749
19 198248
20 201248

About Yukako Yagi

Yukako Yagi is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biophysics and Pulmonary and Respiratory Medicine, having authored 127 papers that have together received 3.6k indexed citations. Recurring topics across this work include AI in cancer detection (73 papers), Radiomics and Machine Learning in Medical Imaging (26 papers), Cell Image Analysis Techniques (23 papers), Digital Imaging for Blood Diseases (12 papers), Image Processing Techniques and Applications (9 papers), Medical Image Segmentation Techniques (9 papers), Cancer Genomics and Diagnostics (7 papers) and Lung Cancer Diagnosis and Treatment (7 papers). The work is most often cited by research in Biophysics (781 citations), Health Informatics (86 citations), Artificial Intelligence (1.7k citations), Radiology, Nuclear Medicine and Imaging (990 citations) and Computer Vision and Pattern Recognition (572 citations). Yukako Yagi has collaborated with scholars based in United States, Japan and Egypt. Frequent co-authors include John R. Gilbertson, Pinky A. Bautista, Jonhan Ho, D.M. Jukic, Anil V. Parwani, Leslie Anthony, Brett E. Bouma, Guillermo J. Tearney, Maristela L. Onozato and Linbo Liu. Their work appears in journals such as Journal of Pathology Informatics, Diagnostic Pathology, Analytical Cellular Pathology, Human Pathology and Journal of Thoracic Oncology.

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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