Le Fu
Impact in
- Health Informatics top 10%
- Obstetrics and Gynecology top 10%
- Endometrial and Cervical Cancer Treatments
Papers in
-
- Cervical Cancer and HPV Research 5
-
- AI in cancer detection 5
- Co-authors
- Haima Yang (6 shared papers)Jian Liu (1 shared paper)Liang Huang (1 shared paper)Qin Yin (1 shared paper)Chunshui Cao (1 shared paper)Boyang Li (1 shared paper)Bin Jiang (1 shared paper)Xingyu Zhao (1 shared paper)
- Journals
- Insights into Imaging (2 papers)Computers in Biology and Medicine (2 papers)Expert Systems with Applications (1 paper)BMC Pregnancy and Childbirth (1 paper)Placenta (1 paper)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Le Fu
24 papers receiving 269 citations
Peers
Comparison fields: 5 of 61
- Health Informatics 13
- Obstetrics and Gynecology 39
- Radiology, Nuclear Medicine and Imaging 59
- Epidemiology 72
- Neurology 14
Countries citing papers authored by Le Fu
This map shows the geographic impact of Le Fu'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 Le Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Le Fu more than expected).
Fields of papers citing papers by Le Fu
This network shows the impact of papers produced by Le Fu. 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 Le Fu. The network helps show where Le Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Le Fu, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 45 | |
| 2 | 2021 | 39 | |
| 3 | 2015 | 28 | |
| 4 | 2021 | 28 | |
| 5 | 2021 | 24 | |
| 6 | 2023 | 16 | |
| 7 | 2013 | 14 | |
| 8 | 2018 | 13 | |
| 9 | 2022 | 9 | |
| 10 | 2022 | 9 | |
| 11 | [Dynamic changes of ROS, MDA and SOD during arsenic-induced neoplastic transformation in human keratinocytes]. | 2015 | 7 |
| 12 | 2020 | 6 | |
| 13 | 2024 | 6 | |
| 14 | 2023 | 5 | |
| 15 | 2024 | 4 | |
| 16 | 2023 | 4 | |
| 17 | 2023 | 3 | |
| 18 | 2024 | 3 | |
| 19 | 2023 | 2 | |
| 20 | 2024 | 1 |
About Le Fu
Le Fu is a scholar working on Epidemiology, Artificial Intelligence, Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health and Public Health, Environmental and Occupational Health, having authored 29 papers that have together received 270 indexed citations. Recurring topics across this work include Cervical Cancer and HPV Research (5 papers), AI in cancer detection (5 papers), Endometrial and Cervical Cancer Treatments (4 papers), Ectopic Pregnancy Diagnosis and Management (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Fetal and Pediatric Neurological Disorders (2 papers), Endometriosis Research and Treatment (2 papers) and Medical Imaging and Analysis (2 papers). The work is most often cited by research in Health Informatics (13 citations), Obstetrics and Gynecology (39 citations), Radiology, Nuclear Medicine and Imaging (59 citations), Epidemiology (72 citations) and Neurology (14 citations). Le Fu has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Haima Yang, Jian Liu, Liang Huang, Qin Yin, Chunshui Cao, Boyang Li, Bin Jiang, Xingyu Zhao, Guangxu Cao and Wei Xia. Their work appears in journals such as Insights into Imaging, Computers in Biology and Medicine, Expert Systems with Applications, BMC Pregnancy and Childbirth and Placenta.
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.