Jing Mei

94 total papers · 833 total citations
58 papers, 430 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 430 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 Tingting Wang 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 417 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Jing Mei	199	103	72	62	57	58	430
Hamid Mukhtar	105 0.5×	30 0.3×	63 0.9×	29 0.5×	60 1.1×	53	488
Tae Min Song	53 0.3×	69 0.7×	19 0.3×	23 0.4×	35 0.6×	33	412
Sharifullah Khan	219 1.1×	41 0.4×	20 0.3×	35 0.6×	161 2.8×	69	448
Hafiz Syed Muhammad Bilal	135 0.7×	78 0.8×	38 0.5×	10 0.2×	66 1.2×	32	462
Beatriz Sainz de Abajo	79 0.4×	47 0.5×	34 0.5×	8 0.1×	67 1.2×	30	495
Karen Day	93 0.5×	121 1.2×	93 1.3×	11 0.2×	18 0.3×	56	486
Muhammad Amith	193 1.0×	19 0.2×	23 0.3×	132 2.1×	55 1.0×	48	452
Juan Antonio Lossio-Ventura	216 1.1×	27 0.3×	21 0.3×	110 1.8×	70 1.2×	37	384
Maryam Zolnoori	143 0.7×	20 0.2×	60 0.8×	60 1.0×	23 0.4×	53	375
Masoud Rouhizadeh	119 0.6×	34 0.3×	24 0.3×	23 0.4×	11 0.2×	39	427

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

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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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