Yan Lou
Impact in
-
- Artificial Intelligence in Healthcare and Education
-
- Ovarian cancer diagnosis and treatment
Papers in
- Oncology 8
- Cancer survivorship and care 6
- Inflammatory Biomarkers in Disease Prognosis 1
-
- Family Support in Illness 2
- Co-authors
- Patsy Yates (6 shared papers)Raymond J. Chan (4 shared papers)Alexandra McCarthy (4 shared papers)Hemei Wang (4 shared papers)Xianhong Huang (1 shared paper)Hongyu Chen (1 shared paper)Qi‐Jun Wu (1 shared paper)Yuhong Zhao (1 shared paper)
In The Last Decade
Yan Lou
19 papers receiving 261 citations
Peers
Comparison fields: 5 of 63
- Health Informatics 10
- Reproductive Medicine 33
- Oncology 65
- Complementary and alternative medicine 14
- Radiology, Nuclear Medicine and Imaging 32
Countries citing papers authored by Yan Lou
This map shows the geographic impact of Yan Lou'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 Yan Lou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Lou more than expected).
Fields of papers citing papers by Yan Lou
This network shows the impact of papers produced by Yan Lou. 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 Yan Lou. The network helps show where Yan Lou may publish in the future.
Co-authors
The 25 scholars most cited alongside Yan Lou, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 86 | |
| 2 | 2019 | 41 | |
| 3 | 2020 | 26 | |
| 4 | 2013 | 21 | |
| 5 | 2013 | 15 | |
| 6 | 2022 | 15 | |
| 7 | 2023 | 12 | |
| 8 | 2022 | 10 | |
| 9 | 2020 | 8 | |
| 10 | 2023 | 8 | |
| 11 | 2024 | 5 | |
| 12 | 2019 | 4 | |
| 13 | 2013 | 3 | |
| 14 | 2015 | 3 | |
| 15 | 2024 | 2 | |
| 16 | 2022 | 2 | |
| 17 | 2015 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2021 | 1 | |
| 20 | 2025 | 0 |
About Yan Lou
Yan Lou is a scholar working on Oncology, Sociology and Political Science, Public Health, Environmental and Occupational Health, Complementary and alternative medicine and Surgery, having authored 25 papers that have together received 266 indexed citations. Recurring topics across this work include Cancer survivorship and care (6 papers), Palliative Care and End-of-Life Issues (3 papers), Nausea and vomiting management (2 papers), Family Support in Illness (2 papers), Inflammatory Biomarkers in Disease Prognosis (1 paper), Pharmacological Effects of Natural Compounds (1 paper), Dysphagia Assessment and Management (1 paper) and Childhood Cancer Survivors' Quality of Life (1 paper). The work is most often cited by research in Health Informatics (10 citations), Reproductive Medicine (33 citations), Oncology (65 citations), Complementary and alternative medicine (14 citations) and Radiology, Nuclear Medicine and Imaging (32 citations). Yan Lou has collaborated with scholars based in China, Australia and Hong Kong. Frequent co-authors include Patsy Yates, Raymond J. Chan, Alexandra McCarthy, Hemei Wang, Xianhong Huang, Hongyu Chen, Qi‐Jun Wu, Yuhong Zhao, Hongzan Sun and Fang-Hua Liu. Their work appears in journals such as Journal of Clinical Nursing, Nursing Open, Cancer Nursing, JCO Global Oncology and Frontiers 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.