Kai Chang

443 total citations
23 papers, 262 citations indexed

About

Kai Chang is a scholar working on Molecular Biology, Artificial Intelligence and Complementary and alternative medicine. According to data from OpenAlex, Kai Chang has authored 23 papers receiving a total of 262 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Artificial Intelligence and 6 papers in Complementary and alternative medicine. Recurrent topics in Kai Chang's work include Traditional Chinese Medicine Studies (6 papers), Biomedical Text Mining and Ontologies (4 papers) and Topic Modeling (4 papers). Kai Chang is often cited by papers focused on Traditional Chinese Medicine Studies (6 papers), Biomedical Text Mining and Ontologies (4 papers) and Topic Modeling (4 papers). Kai Chang collaborates with scholars based in China, United Kingdom and United States. Kai Chang's co-authors include Zixin Shu, Xuezhong Zhou, Fake Li, Shaoli Deng, Shaojun Yang, Kejun Zhang, Ming Chen, Shuangrong Jia, Baoyan Liu and Kuo Yang and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Sustainability and BioMed Research International.

In The Last Decade

Kai Chang

17 papers receiving 260 citations

Peers

Kai Chang
Xiaoqin Li China
Rintu Kutum India
Huling Li China
Ying Dong China
Zhandong Li China
Chaogang Fan China
Tieling Li China
Seongoh Park South Korea
Die Dai China
Changlu Qi China
Xiaoqin Li China
Kai Chang
Citations per year, relative to Kai Chang Kai Chang (= 1×) peers Xiaoqin Li

Countries citing papers authored by Kai Chang

Since Specialization
Citations

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

Fields of papers citing papers by Kai Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Kai Chang. A scholar is included among the top collaborators of Kai Chang 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 Kai Chang. Kai Chang 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
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Liu, Yiming, Haoyu Tian, Kai Chang, et al.. (2025). LLM4DEU: Fine Tuning Large Language Model for Medical Diagnosis in Outpatient and Emergency Department Visits of Neurosurgery. Tsinghua Science & Technology. 30(6). 2487–2504.
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Zheng, Qiguang, et al.. (2024). Deep representation learning from electronic medical records identifies distinct symptom based subtypes and progression patterns for COVID-19 prognosis. International Journal of Medical Informatics. 191. 105555–105555. 1 indexed citations
5.
Chang, Kai, et al.. (2024). Study on Resilience Evaluation for Construction Management of Major Railway Projects. Buildings. 14(3). 732–732. 7 indexed citations
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Xin, Dong, Zixin Shu, Pengcheng Yang, et al.. (2024). Lingdan: enhancing encoding of traditional Chinese medicine knowledge for clinical reasoning tasks with large language models. Journal of the American Medical Informatics Association. 31(9). 2019–2029. 27 indexed citations
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Xu, Ning, Kai Chang, Jinlong Yu, et al.. (2023). Classification Characteristics of COPD Based on Combination of Disease and Syndrome in Real World. 30. 4667–4674.
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Chang, Kai, Ting Jia, Yana Zhou, et al.. (2023). Validation and Refinement of Two Interpretable Models for Coronavirus Disease 2019 Prognosis Prediction. World Journal of Traditional Chinese Medicine. 9(2). 191–200. 2 indexed citations
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Xu, Ning, Haibin Yu, Zixin Shu, et al.. (2022). Add-on Chinese medicine for hospitalized chronic obstructive pulmonary disease (CHOP): A cohort study of hospital registry. Phytomedicine. 109. 154586–154586. 5 indexed citations
12.
Dong, Xin Luna, Yi Zheng, Zixin Shu, et al.. (2022). TCMPR: TCM Prescription Recommendation Based on Subnetwork Term Mapping and Deep Learning. BioMed Research International. 2022(1). 4845726–4845726. 25 indexed citations
13.
Heald, Adrian, Kai Chang, Ting Jia, et al.. (2021). Longitudinal clinical trajectory analysis of individuals before and after diagnosis of Type 2 Diabetes Mellitus (T2DM) indicates that vascular problems start early. International Journal of Clinical Practice. 75(11). e14695–e14695. 2 indexed citations
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Wang, Ning, Yonghong Peng, Kuo Yang, et al.. (2021). Network Patterns of Herbal Combinations in Traditional Chinese Clinical Prescriptions. Frontiers in Pharmacology. 11. 590824–590824. 14 indexed citations
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Shu, Zixin, Kai Chang, Yana Zhou, et al.. (2021). 2021 Integrative Medicine & Health Symposium Abstracts. Global Advances in Health and Medicine. 10. 4 indexed citations
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Yang, Kuo, Zixin Shu, Jingjing Wang, et al.. (2020). Integrated network analysis of symptom clusters across disease conditions. Journal of Biomedical Informatics. 107. 103482–103482. 13 indexed citations
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Shu, Zixin, Yana Zhou, Kai Chang, et al.. (2020). Clinical features and the traditional Chinese medicine therapeutic characteristics of 293 COVID-19 inpatient cases. Frontiers of Medicine. 14(6). 760–775. 38 indexed citations
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Yang, Kuo, Yi Zheng, Kai Chang, et al.. (2020). PDGNet: Predicting Disease Genes Using a Deep Neural Network With Multi-View Features. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(1). 575–584. 24 indexed citations
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Li, Fake, Jie Luo, Huan Xu, et al.. (2019). Early secreted antigenic target 6-kDa from Mycobacterium tuberculosis enhanced the protective innate immunity of macrophages partially via HIF1α. Biochemical and Biophysical Research Communications. 522(1). 26–32. 7 indexed citations
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Yang, Shaojun, Fake Li, Shuangrong Jia, et al.. (2015). Early Secreted Antigen ESAT-6 of Mycobacterium Tuberculosis Promotes Apoptosis of Macrophages via Targeting the MicroRNA155-SOCS1 Interaction. Cellular Physiology and Biochemistry. 35(4). 1276–1288. 76 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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