Chaoyi Wu

1.4k total citations · 1 hit paper
21 papers, 426 citations indexed

About

Chaoyi Wu is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chaoyi Wu has authored 21 papers receiving a total of 426 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chaoyi Wu's work include Topic Modeling (6 papers), COVID-19 diagnosis using AI (5 papers) and Machine Learning in Healthcare (4 papers). Chaoyi Wu is often cited by papers focused on Topic Modeling (6 papers), COVID-19 diagnosis using AI (5 papers) and Machine Learning in Healthcare (4 papers). Chaoyi Wu collaborates with scholars based in China, United States and Germany. Chaoyi Wu's co-authors include Ya Zhang, Xiaoman Zhang, Weidi Xie, Yanfeng Wang, Weidi Xie, Weixiong Lin, Yanfeng Wang, Xiaoman Zhang, Pengcheng Qiu and Haicheng Wang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Science Advances.

In The Last Decade

Chaoyi Wu

18 papers receiving 420 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

PMC-LLaMA: toward building open-source language models for medicine

2024 132 citations Chaoyi Wu, Weixiong Lin et al. Journal of the American Medical Informatics Association profile →

Peers

Chaoyi Wu

AI

RNMI

MB

HI

CVPR

Mohammad Asadur Rahman Bangladesh

Sungmin Lim South Korea

Longxi Zhou Saudi Arabia

Miao Wu China

Rajagopala Chadaga India

Hui Zong China

William Wasswa Uganda

Krithi Pushpanathan Singapore

Sarvesh Soni United States

Ritwik Sinha United States

Mohammad Asadur Rahman Bangladesh

Chaoyi Wu

119 ×0.6

AI

147 ×1.4

RNMI

71 ×0.9

MB

35 ×0.4

HI

39 ×0.6

CVPR

Citations per year, relative to Chaoyi Wu Chaoyi Wu (= 1×) peers Mohammad Asadur Rahman

Countries citing papers authored by Chaoyi Wu

Since Specialization

Citations

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

Fields of papers citing papers by Chaoyi Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chaoyi Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Chaoyi Wu. A scholar is included among the top collaborators of Chaoyi Wu 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 Chaoyi Wu. Chaoyi Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Wu, Chaoyi, Shuyu Liu, Yanjie Fan, et al.. (2025). Quantifying the reasoning abilities of LLMs on clinical cases. Nature Communications. 16(1). 9799–9799.

2.

Zhang, Yao, Chaoyi Wu, Xiaoman Zhang, et al.. (2025). Large-vocabulary segmentation for medical images with text prompts. npj Digital Medicine. 8(1). 566–566. 1 indexed citations

3.

Gao, Jian, et al.. (2025). Complex brain networks mediation of neuroticism and extraversion on obsessive-compulsive disorder. Journal of Affective Disorders. 390. 119795–119795.

4.

Zhang, Xiaoman, Chaoyi Wu, Weiwei Tian, et al.. (2025). Development of a large-scale grounded vision language dataset for chest CT analysis. Scientific Data. 12(1). 1636–1636. 1 indexed citations

5.

Wu, Chaoyi, Xiaoman Zhang, Ya Zhang, et al.. (2025). Towards generalist foundation model for radiology by leveraging web-scale 2D&3D medical data. Nature Communications. 16(1). 7866–7866. 11 indexed citations

6.

Wu, Chaoyi, et al.. (2025). A framework for parsing psychopathological heterogeneity: initial application in a large-scale unselected community sample. BMC Psychiatry. 25(1). 619–619.

7.

Wu, Chaoyi, Xiaoman Zhang, Yao Zhang, et al.. (2025). UniBrain: Universal Brain MRI diagnosis with hierarchical knowledge-enhanced pre-training. Computerized Medical Imaging and Graphics. 122. 102516–102516. 3 indexed citations

8.

Wu, Chaoyi, Jinxin Liu, Hongfei Gu, et al.. (2025). Towards evaluating and building versatile large language models for medicine. npj Digital Medicine. 8(1). 58–58. 8 indexed citations

9.

Wu, Chaoyi, et al.. (2024). RaTEScore: A Metric for Radiology Report Generation. 15004–15019. 5 indexed citations

10.

Wu, Chaoyi, Xiaoman Zhang, Yuehua Li, et al.. (2024). Large-scale long-tailed disease diagnosis on radiology images. Nature Communications. 15(1). 10147–10147. 5 indexed citations

11.

Qiu, Pengcheng, Chaoyi Wu, Xiaoman Zhang, et al.. (2024). Towards building multilingual language model for medicine. Nature Communications. 15(1). 8384–8384. 38 indexed citations

12.

Wu, Chaoyi, Yayu Wang, Xinjiani Chen, et al.. (2024). The first bioactive (angiotensin-converting enzyme-inhibitory) peptide isolated from pearl matrix protein. Heliyon. 10(7). e28060–e28060. 4 indexed citations

13.

Zhang, Xiaoman, Chaoyi Wu, Weixiong Lin, et al.. (2024). Development of a large-scale medical visual question-answering dataset. SHILAP Revista de lepidopterología. 4(1). 277–277. 9 indexed citations

14.

Wu, Chaoyi, Weixiong Lin, Xiaoman Zhang, et al.. (2024). PMC-LLaMA: toward building open-source language models for medicine. Journal of the American Medical Informatics Association. 31(9). 1833–1843. 132 indexed citations breakdown →

15.

Zhang, Xiaoman, Chaoyi Wu, Ya Zhang, Weidi Xie, & Yanfeng Wang. (2023). Knowledge-enhanced visual-language pre-training on chest radiology images. Nature Communications. 14(1). 4542–4542. 86 indexed citations

16.

Wu, Chaoyi, et al.. (2023). Metabolomic Analysis of Polymicrobial Wound Infections and an Associated Adhesive Bandage. Journal of the American Society for Mass Spectrometry. 34(9). 1847–1857. 1 indexed citations

17.

Wu, Chaoyi, Feng Chang, Xiao Su, et al.. (2022). Integrating features from lymph node stations for metastatic lymph node detection. Computerized Medical Imaging and Graphics. 101. 102108–102108. 3 indexed citations

18.

Hossain, Ekram, et al.. (2020). Mapping of host-parasite-microbiome interactions reveals metabolic determinants of tropism and tolerance in Chagas disease. Science Advances. 6(30). 46 indexed citations

19.

Gibaut, Quentin M. R., Yanting Guo, Ekram Hossain, et al.. (2020). Local Phenomena Shape Backyard Soil Metabolite Composition. Metabolites. 10(3). 86–86. 12 indexed citations

20.

Wu, Tao, Yue Wang, Jie An, et al.. (2019). M1‐polarized alveolar macrophages are crucial in a mouse model of transfusion‐related acute lung injury. Transfusion. 60(2). 303–316. 18 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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