Fang‐I Lu

44 papers receiving 1.1k citations

Peers

Fang‐I Lu
Comparison fields: 5 of 89
  • Health Informatics 26
  • Oncology 392
  • Cancer Research 201
  • Pathology and Forensic Medicine 189
  • Radiology, Nuclear Medicine and Imaging 219
Replace Ji Hyun Chang with:
Ji Hyun Chang South Korea
Ahrong Kim South Korea
Tarjei S. Hveem Norway
Yannick Boursin France
Kazuhiro Tabata Japan
David Brandão France
Thing Rinda Soong United States
Ines Nikolovski United States
Aparna Harbhajanka United States
Fang‐I Lu relative to Ji Hyun Chang South Korea Ji Hyun Chang's profile →
Citations per field
00.5×2×2.6×
Ji Hyun Chang · 1×
Citations per year

Countries citing papers authored by Fang‐I Lu

Since Specialization
Citations

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

Fields of papers citing papers by Fang‐I Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fang‐I Lu. 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 Fang‐I Lu. The network helps show where Fang‐I Lu may publish in the future.

Co-authors

The 25 scholars most cited alongside Fang‐I Lu, 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 Fang‐I Lu Line = papers co-authored together Fang‐I Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021193
2 2010162
3 201974
4 202158
5 201257
6 202056
7 201750
8 202139
9 201838
10 202138
11 201533
12 202232
13 202130
14 201928
15 202320
16 201720
17 201319
18 201818
19 202116
20 202216

About Fang‐I Lu

Fang‐I Lu is a scholar working on Cancer Research, Radiology, Nuclear Medicine and Imaging, Oncology, Pathology and Forensic Medicine and Public Health, Environmental and Occupational Health, having authored 45 papers that have together received 1.1k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (12 papers), Cancer Genomics and Diagnostics (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), AI in cancer detection (5 papers), Breast Lesions and Carcinomas (4 papers), Cancer Immunotherapy and Biomarkers (3 papers), HER2/EGFR in Cancer Research (3 papers) and Ovarian cancer diagnosis and treatment (2 papers). The work is most often cited by research in Health Informatics (26 citations), Oncology (392 citations), Cancer Research (201 citations), Pathology and Forensic Medicine (189 citations) and Radiology, Nuclear Medicine and Imaging (219 citations). Fang‐I Lu has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Elzbieta A. Slodkowska, Sharon Nofech‐Mozes, William T. Tran, David Andrew Owen, Douglas L. Webber, Dmitry A. Turbin, Ali Sadeghi Naini, Wedad M. Hanna, Sonal G. Gandhi and Andrew Lagree. Their work appears in journals such as Archives of Pathology & Laboratory Medicine, Scientific Reports, Breast Cancer Research and Treatment, npj Breast Cancer and Journal of Ultrasound in Medicine.

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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