Jing Ye
Impact in
- Signal Processing top 5%
- Time Series Analysis and Forecasting
- Epidemiology top 10%
- Cervical Cancer and HPV Research
- Hepatitis B Virus Studies
- Autophagy in Disease and Therapy
Papers in
- Epidemiology 17
- Cervical Cancer and HPV Research 8
- Hepatitis B Virus Studies 3
- Pneumonia and Respiratory Infections 2
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- AI in cancer detection 6
- Co-authors
- Bryan Hooi (1 shared paper)Xueqi Cheng (1 shared paper)Shenghua Liu (1 shared paper)Bin Zhou (1 shared paper)Xiaodong Cheng (5 shared papers)Xing Xie (5 shared papers)Weiguo Lü (4 shared papers)Xiaojing Chen (3 shared papers)
- Journals
- Medicine (2 papers)Frontiers in Pharmacology (2 papers)Frontiers in Neuroscience (2 papers)BMC Cancer (2 papers)Journal of Zhejiang University SCIENCE B (2 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Jing Ye
48 papers receiving 684 citations
Peers
Comparison fields: 5 of 102
- Signal Processing 118
- Epidemiology 238
- Health Informatics 9
- Artificial Intelligence 198
- Microbiology 22
Countries citing papers authored by Jing Ye
This map shows the geographic impact of Jing Ye'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 Jing Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Ye more than expected).
Fields of papers citing papers by Jing Ye
This network shows the impact of papers produced by Jing Ye. 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 Jing Ye. The network helps show where Jing Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Jing Ye, 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 185 | |
| 2 | 2010 | 78 | |
| 3 | 2023 | 38 | |
| 4 | 2021 | 35 | |
| 5 | 2018 | 32 | |
| 6 | 2020 | 27 | |
| 7 | 2022 | 21 | |
| 8 | 2017 | 20 | |
| 9 | 2019 | 18 | |
| 10 | 2023 | 16 | |
| 11 | 2015 | 15 | |
| 12 | 2019 | 14 | |
| 13 | 2012 | 13 | |
| 14 | 2018 | 12 | |
| 15 | 2017 | 12 | |
| 16 | [Analysis of correlative factors and prevalence on China's youth myopia]. | 2010 | 11 |
| 17 | 2021 | 10 | |
| 18 | 2022 | 10 | |
| 19 | 2010 | 9 | |
| 20 | 2018 | 8 |
About Jing Ye
Jing Ye is a scholar working on Epidemiology, Artificial Intelligence, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 53 papers that have together received 696 indexed citations. Recurring topics across this work include Cervical Cancer and HPV Research (8 papers), AI in cancer detection (6 papers), Functional Brain Connectivity Studies (4 papers), Medical Image Segmentation Techniques (3 papers), Hepatitis B Virus Studies (3 papers), Pneumonia and Respiratory Infections (2 papers), Phonetics and Phonology Research (2 papers) and Genital Health and Disease (2 papers). The work is most often cited by research in Signal Processing (118 citations), Epidemiology (238 citations), Health Informatics (9 citations), Artificial Intelligence (198 citations) and Microbiology (22 citations). Jing Ye has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Bryan Hooi, Xueqi Cheng, Shenghua Liu, Bin Zhou, Xiaodong Cheng, Xing Xie, Weiguo Lü, Xiaojing Chen, Feng Ye and Jingtao Wu. Their work appears in journals such as Medicine, Frontiers in Pharmacology, Frontiers in Neuroscience, BMC Cancer and Journal of Zhejiang University SCIENCE B.
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.