Fang‐I Lu
Impact in
- Health Informatics top 5%
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- Genetic factors in colorectal cancer
- Breast Lesions and Carcinomas
Papers in
-
- Breast Cancer Treatment Studies 16
- Cancer Genomics and Diagnostics 5
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- Radiomics and Machine Learning in Medical Imaging 10
- Co-authors
- Elzbieta Slodkowska (14 shared papers)Sharon Nofech‐Mozes (12 shared papers)Douglas Webber (1 shared paper)David Owen (1 shared paper)Dmitry Turbin (1 shared paper)William T. Tran (11 shared papers)Ali Sadeghi‐Naini (8 shared papers)Wedad Hanna (7 shared papers)
- Journals
- Archives of Pathology & Laboratory Medicine (4 papers)Scientific Reports (3 papers)Breast Cancer Research and Treatment (3 papers)Modern Pathology (2 papers)The American Journal of Surgical Pathology (2 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Fang‐I Lu
39 papers receiving 785 citations
Peers
Comparison fields: 5 of 86
- Health Informatics 27
- Pathology and Forensic Medicine 221
- Cancer Research 181
- Oncology 309
- Radiology, Nuclear Medicine and Imaging 244
Countries citing papers authored by Fang‐I Lu
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
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.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 152 | |
| 2 | 2019 | 60 | |
| 3 | 2012 | 51 | |
| 4 | 2020 | 48 | |
| 5 | 2021 | 48 | |
| 6 | 2017 | 46 | |
| 7 | 2015 | 31 | |
| 8 | 2021 | 31 | |
| 9 | 2018 | 30 | |
| 10 | 2021 | 29 | |
| 11 | 2021 | 26 | |
| 12 | 2022 | 24 | |
| 13 | 2019 | 24 | |
| 14 | 2023 | 19 | |
| 15 | 2017 | 18 | |
| 16 | 2013 | 16 | |
| 17 | 2018 | 15 | |
| 18 | 2022 | 15 | |
| 19 | 2022 | 13 | |
| 20 | 2021 | 11 |
About Fang‐I Lu
Fang‐I Lu is a scholar working on Cancer Research, Radiology, Nuclear Medicine and Imaging, Oncology, Artificial Intelligence and Pathology and Forensic Medicine, having authored 41 papers that have together received 794 indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (16 papers), AI in cancer detection (11 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Breast Lesions and Carcinomas (8 papers), Cancer Genomics and Diagnostics (5 papers), HER2/EGFR in Cancer Research (4 papers), Cancer and Skin Lesions (3 papers) and Genetic factors in colorectal cancer (2 papers). The work is most often cited by research in Health Informatics (27 citations), Pathology and Forensic Medicine (221 citations), Cancer Research (181 citations), Oncology (309 citations) and Radiology, Nuclear Medicine and Imaging (244 citations). Fang‐I Lu has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Elzbieta Slodkowska, Sharon Nofech‐Mozes, Douglas Webber, David Owen, Dmitry Turbin, William T. Tran, Ali Sadeghi‐Naini, Wedad Hanna, Sonal Gandhi and Andrew Lagree. Their work appears in journals such as Archives of Pathology & Laboratory Medicine, Scientific Reports, Breast Cancer Research and Treatment, Modern Pathology and The American Journal of Surgical Pathology.
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.