Min Jiang

3.1k total citations
73 papers, 2.1k citations indexed

About

Min Jiang is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Min Jiang has authored 73 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 40 papers in Artificial Intelligence and 8 papers in Genetics. Recurrent topics in Min Jiang's work include Biomedical Text Mining and Ontologies (38 papers), Topic Modeling (30 papers) and Natural Language Processing Techniques (25 papers). Min Jiang is often cited by papers focused on Biomedical Text Mining and Ontologies (38 papers), Topic Modeling (30 papers) and Natural Language Processing Techniques (25 papers). Min Jiang collaborates with scholars based in United States, China and Canada. Min Jiang's co-authors include Hua Xu, Yonghui Wu, Joshua C. Denny, Buzhou Tang, Yukun Chen, Hongfang Liu, Yaoyun Zhang, Ergin Soysal, Jingqi Wang and Serguei Pakhomov and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Chemistry of Materials.

In The Last Decade

Min Jiang

70 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Min Jiang United States 25 1.3k 1.2k 200 135 99 73 2.1k
Matthias Samwald Austria 22 759 0.6× 660 0.6× 113 0.6× 237 1.8× 30 0.3× 70 1.5k
Paea LePendu United States 21 504 0.4× 571 0.5× 156 0.8× 76 0.6× 50 0.5× 40 1.9k
Jianying Hu United States 25 1.0k 0.8× 590 0.5× 490 2.5× 57 0.4× 61 0.6× 77 2.6k
C Friedman United States 26 1.5k 1.2× 1.7k 1.4× 487 2.4× 66 0.5× 36 0.4× 43 2.8k
Marianthi Markatou United States 31 702 0.5× 663 0.6× 201 1.0× 44 0.3× 81 0.8× 87 2.7k
Jon Duke United States 23 463 0.4× 465 0.4× 490 2.5× 112 0.8× 95 1.0× 52 2.2k
Peggy Peissig United States 28 844 0.6× 972 0.8× 531 2.7× 115 0.9× 107 1.1× 91 2.8k
Juan M. Banda United States 18 568 0.4× 296 0.2× 193 1.0× 40 0.3× 48 0.5× 62 1.5k
David Madigan United States 24 690 0.5× 335 0.3× 249 1.2× 81 0.6× 103 1.0× 47 2.6k
Richard D. Boyce United States 23 279 0.2× 487 0.4× 186 0.9× 252 1.9× 47 0.5× 99 1.6k

Countries citing papers authored by Min Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Min Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Min Jiang. A scholar is included among the top collaborators of Min Jiang 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 Min Jiang. Min Jiang 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, Le, Huan Zhou, Zheng Jiao, et al.. (2025). Insights From a User Experience‐Focused Virtual Study on the Feasibility and Challenges of Decentralized Clinical Trials. Clinical and Translational Science. 18(8). e70307–e70307. 1 indexed citations
2.
Jiang, Min, Yang Yu, Jihong Bian, et al.. (2025). Explosion induced domino effect assessment in the process industries: A machine learning approach to improve probit models. Journal of Loss Prevention in the Process Industries. 98. 105714–105714. 1 indexed citations
3.
Jiang, Min, et al.. (2024). A cause-effect relationship between uterine diseases and breast cancer: A bidirectional Mendelian randomization study. Heliyon. 10(18). e38130–e38130. 1 indexed citations
4.
5.
Jiang, Min, et al.. (2021). Incorporating multi-level CNN and attention mechanism for Chinese clinical named entity recognition. Journal of Biomedical Informatics. 116. 103737–103737. 59 indexed citations
6.
Lu, Yujie, Wen‐Jie Wang, Min Jiang, et al.. (2019). Prognostic values of platelet-associated indicators in advanced breast cancer. Translational Cancer Research. 8(4). 1326–1335. 1 indexed citations
7.
Soysal, Ergin, Jeremy L. Warner, Jingqi Wang, et al.. (2019). Developing Customizable Cancer Information Extraction Modules for Pathology Reports Using CLAMP. Studies in health technology and informatics. 264. 1041–1045. 9 indexed citations
8.
Jiang, Min, T.M. Sanger, & Xiong Liu. (2019). Combining Contextualized Embeddings and Prior Knowledge for Clinical Named Entity Recognition: Evaluation Study. JMIR Medical Informatics. 7(4). e14850–e14850. 24 indexed citations
9.
Li, Yan, et al.. (2014). Observation on the Changes of Sleep Structure in 82 Patients with Epilepsy by Polysomnography Combined with Long-term Video Electroencephalogram. SHILAP Revista de lepidopterología. 1 indexed citations
10.
Huang, Ou, Min Jiang, Xiaosong Chen, et al.. (2014). Prognostic Factors of Survival in Pathologic Incomplete Response Patients with Locally Advanced Breast Cancer After Neoadjuvant Chemotherapy. Cell Biochemistry and Biophysics. 71(2). 1181–1190. 2 indexed citations
11.
Zhang, Yaoyun, Trevor Cohen, Min Jiang, Buzhou Tang, & Hua Xu. (2013). Evaluation of Vector Space Models for Medical Disorders Information Retrieval.. CLEF (Working Notes). 1179. 2 indexed citations
12.
Tang, Buzhou, Yonghui Wu, Min Jiang, Joshua C. Denny, & Hua Xu. (2013). Recognizing and Encoding Disorder Concepts in Clinical Text using Machine Learning and Vector Space Model. CLEF (Working Notes). 1179. 26 indexed citations
13.
Wu, Yonghui, Buzhou Tang, Min Jiang, et al.. (2013). Clinical Acronym/Abbreviation Normalization using a Hybrid Approach.. CLEF (Working Notes). 1179. 14 indexed citations
14.
Feng, QiPing, Lan Jiang, Otito F. Iwuchukwu, et al.. (2013). Characterization of Statin Dose Response in Electronic Medical Records. Clinical Pharmacology & Therapeutics. 95(3). 331–338. 25 indexed citations
15.
Huang, Ou, Min Jiang, Xi Zhang, et al.. (2013). Grb14 as an Independent Good Prognosis Factor for Breast Cancer Patients Treated with Neoadjuvant Chemotherapy. Japanese Journal of Clinical Oncology. 43(11). 1064–1072. 10 indexed citations
16.
Fan, Jungwei, Min Jiang, Rashmi Prasad, et al.. (2013). Syntactic parsing of clinical text: guideline and corpus development with handling ill-formed sentences. Journal of the American Medical Informatics Association. 20(6). 1168–1177. 20 indexed citations
17.
Tang, Buzhou, Yonghui Wu, Min Jiang, et al.. (2013). A hybrid system for temporal information extraction from clinical text. Journal of the American Medical Informatics Association. 20(5). 828–835. 89 indexed citations
18.
Lu, Yanxin, Hua Xu, Neeraja B. Peterson, et al.. (2012). Extracting epidemiologic exposure and outcome terms from literature using machine learning approaches. International Journal of Data Mining and Bioinformatics. 6(4). 447–447. 4 indexed citations
19.
Jiang, Min & Serge B. Provost. (2011). Improved orthogonal polynomial density estimates. Journal of Statistical Computation and Simulation. 81(11). 1495–1516. 2 indexed citations
20.
Jiang, Min, Yukun Chen, Mei Liu, et al.. (2011). A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries. Journal of the American Medical Informatics Association. 18(5). 601–606. 214 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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