Jing Mei

842 total citations
58 papers, 434 citations indexed

About

Jing Mei is a scholar working on Artificial Intelligence, Molecular Biology and Health Information Management. According to data from OpenAlex, Jing Mei has authored 58 papers receiving a total of 434 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 15 papers in Molecular Biology and 14 papers in Health Information Management. Recurrent topics in Jing Mei's work include Machine Learning in Healthcare (14 papers), Biomedical Text Mining and Ontologies (11 papers) and Semantic Web and Ontologies (10 papers). Jing Mei is often cited by papers focused on Machine Learning in Healthcare (14 papers), Biomedical Text Mining and Ontologies (11 papers) and Semantic Web and Ontologies (10 papers). Jing Mei collaborates with scholars based in China, United States and Canada. Jing Mei's co-authors include Pengwei Hu, Shaochun Li, Hui Su, Chenhao Lin, Henry W. C. Leung, Jie Zhou, Harold Boley, Zhaomeng Niu, Guotong Xie and Haifeng Liu and has published in prestigious journals such as Journal of Medicinal Chemistry, Aquaculture and European Journal of Pharmacology.

In The Last Decade

Jing Mei

51 papers receiving 420 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jing Mei China 10 200 103 72 62 58 58 434
Sandra Bringay France 15 270 1.4× 173 1.7× 27 0.4× 54 0.9× 42 0.7× 62 725
Samah Fodeh United States 14 225 1.1× 67 0.7× 43 0.6× 64 1.0× 12 0.2× 43 539
Paweł Matykiewicz United States 12 507 2.5× 288 2.8× 42 0.6× 183 3.0× 88 1.5× 18 820
Hong-Jie Dai Taiwan 15 473 2.4× 61 0.6× 92 1.3× 328 5.3× 24 0.4× 65 755
Cyril Grouin France 13 321 1.6× 28 0.3× 59 0.8× 239 3.9× 20 0.3× 49 488
Sharifullah Khan Pakistan 11 220 1.1× 42 0.4× 20 0.3× 35 0.6× 14 0.2× 69 449
William Van Woensel Canada 8 71 0.4× 17 0.2× 23 0.3× 26 0.4× 47 0.8× 37 271
Maja Hadzic Australia 11 154 0.8× 32 0.3× 24 0.3× 68 1.1× 16 0.3× 38 357
Juan Antonio Lossio-Ventura United States 11 218 1.1× 28 0.3× 21 0.3× 110 1.8× 9 0.2× 37 391
Ugur Kursuncu United States 8 191 1.0× 172 1.7× 17 0.2× 18 0.3× 46 0.8× 16 362

Countries citing papers authored by Jing Mei

Since Specialization
Citations

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

Fields of papers citing papers by Jing Mei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jing Mei. 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 Mei. The network helps show where Jing Mei may publish in the future.

Co-authorship network of co-authors of Jing Mei

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Mei. A scholar is included among the top collaborators of Jing Mei based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jing Mei. Jing Mei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Mengyuan, Jing Mei, Xiaohong Zhang, & Jun Liu. (2025). Neural networks based on interval-valued pseudo overlap and grouping functions with applications to fuzzy reasoning and image classification. Applied Soft Computing. 181. 113405–113405.
2.
Liu, Cong & Jing Mei. (2025). HFGGRFN: High-frequency guided group recurrent feedback network for hyperspectral image fusion. Optics & Laser Technology. 188. 112923–112923.
3.
Yang, Shenglong, Jing Mei, Kui Liu, et al.. (2025). Facile conversion from spent graphite to N-doped graphite with high cycling performance. Journal of Energy Storage. 119. 116399–116399. 2 indexed citations
4.
Zhang, Yeqing, et al.. (2024). Protective effect of Astragaloside II against lung injury in COPD based on mTORC1/GSK-3β signaling pathway. European Journal of Pharmacology. 988. 177214–177214. 1 indexed citations
5.
Nie, Lulin, Kaiwu He, Qing Li, et al.. (2024). Tetramethylpyrazine Nitrone alleviates D-galactose-induced murine skeletal muscle aging and motor deficits by activating the AMPK signaling pathway. Biomedicine & Pharmacotherapy. 173. 116415–116415. 8 indexed citations
6.
Mei, Jing, Tao Wang, Kai Long, et al.. (2023). Assessing the suitability of three purple soils for aquaculture by physiological responses in freshwater bivalves (Hyriopsis cumingii). Aquaculture. 575. 739765–739765. 3 indexed citations
7.
Qingqing, Zhou, Jing Mei, Xiaobo Yu, et al.. (2023). Elucidation on potential utilization of Forsythia suspensa fruits in freshwater bivalve (Hyriopsis cumingii) culture against Aeromonas veronii infection. Industrial Crops and Products. 201. 116963–116963. 1 indexed citations
8.
Mei, Jing, et al.. (2021). MFCNet: Mining Features Context Network for RGB–IR Person Re-Identification. Future Internet. 13(11). 290–290. 1 indexed citations
9.
Hu, Pengwei, Yu‐An Huang, Jing Mei, et al.. (2021). Learning from low-rank multimodal representations for predicting disease-drug associations. BMC Medical Informatics and Decision Making. 21(S1). 308–308. 12 indexed citations
10.
Tang, Zefang, et al.. (2021). Disease network delineates the disease progression profile of cardiovascular diseases. Journal of Biomedical Informatics. 115. 103686–103686. 7 indexed citations
11.
Niu, Zhaomeng, et al.. (2020). Chinese Public’s Engagement in Preventive and Intervening Health Behaviors During the Early Breakout of COVID-19: Cross-Sectional Study. Journal of Medical Internet Research. 22(8). e19995–e19995. 34 indexed citations
12.
Li, Jing, et al.. (2020). Accelerating Epidemiological Investigation Analysis by Using NLP and Knowledge Reasoning: A Case Study on COVID-19.. PubMed. 2020. 1258–1267. 4 indexed citations
13.
Niu, Zhaomeng, et al.. (2020). A Cross-Cultural Comparison of an Extended Planned Risk Information Seeking Model on Mental Health Among College Students: Cross-Sectional Study. Journal of Medical Internet Research. 22(5). e15817–e15817. 13 indexed citations
14.
Li, Weiwei, Ying‐Ying Shen, Dong‐Wan Chen, et al.. (2019). Genetic Association Between NGFR, ADAM17 Gene Polymorphism, and Parkinson’s Disease in the Chinese Han Population. Neurotoxicity Research. 36(3). 463–471. 8 indexed citations
15.
Mei, Jing, et al.. (2019). Knowledge Learning Symbiosis for Developing Risk Prediction Models from Regional EHR Repositories. Studies in health technology and informatics. 264. 258–262. 5 indexed citations
16.
Du, Xin, Jing Mei, Wen Sun, et al.. (2019). Outcome-Driven Clustering of Acute Coronary Syndrome Patients Using Multi-Task Neural Network with Attention. Studies in health technology and informatics. 264. 457–461. 5 indexed citations
17.
18.
Zhang, Yuan, Peiyao Li, Jing Mei, et al.. (2019). Predicting Prevalence of Respiratory Disease with Multi-task Gaussian Process: A Case Study in East China. 1–3. 2 indexed citations
19.
Mei, Jing, Shiwan Zhao, Gang Hu, et al.. (2017). Applying Risk Models on Patients with Unknown Predictor Values: An Incremental Learning Approach. Studies in health technology and informatics. 245. 639–643. 1 indexed citations
20.
Mei, Jing, et al.. (2008). UMRR: towards an enterprise-wide web of models. International Semantic Web Conference. 44–45. 2 indexed citations

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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