Jianyi Dai

2.3k total citations · 1 hit paper
12 papers, 1.2k citations indexed

About

Jianyi Dai is a scholar working on Infectious Diseases, Epidemiology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jianyi Dai has authored 12 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Infectious Diseases, 5 papers in Epidemiology and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jianyi Dai's work include COVID-19 Clinical Research Studies (7 papers), SARS-CoV-2 and COVID-19 Research (5 papers) and COVID-19 diagnosis using AI (4 papers). Jianyi Dai is often cited by papers focused on COVID-19 Clinical Research Studies (7 papers), SARS-CoV-2 and COVID-19 Research (5 papers) and COVID-19 diagnosis using AI (4 papers). Jianyi Dai collaborates with scholars based in China and United States. Jianyi Dai's co-authors include Qiqi Cao, Ashan Pan, Fuhua Yan, Le Qin, Zenghui Cheng, Wenjie Yang, Qingfeng Sun, Xiaoyang Wang, Jieming Qu and Chenchan Hu and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Frontiers in Microbiology and Medicine.

In The Last Decade

Jianyi Dai

12 papers receiving 1.2k citations

Hit Papers

Clinical characteristics and imaging manifestations of th... 2020 2026 2022 2024 2020 200 400 600

Peers

Jianyi Dai
Qiqi Cao China
Sana Salehi United States
S. Balakrishnan United States
Ling Sang China
Jianyi Dai
Citations per year, relative to Jianyi Dai Jianyi Dai (= 1×) peers Nannan Shi

Countries citing papers authored by Jianyi Dai

Since Specialization
Citations

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

Fields of papers citing papers by Jianyi Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianyi Dai

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

All Works

12 of 12 papers shown
1.
Wu, Lianpeng, Machao Li, Jianyi Dai, et al.. (2024). High-throughput nanopore targeted sequencing for efficient drug resistance assay of Mycobacterium tuberculosis. Frontiers in Microbiology. 15. 1331656–1331656. 5 indexed citations
2.
He, Guiqing, Jing Wu, Jianping Huang, et al.. (2021). Clinical features and viral RNA shedding of imported and local cases with COVID-19 in Wenzhou, China. Medicine. 100(11). e24826–e24826. 1 indexed citations
3.
Cheng, Zenghui, Le Qin, Qiqi Cao, et al.. (2020). Quantitative computed tomography of the coronavirus disease 2019 (COVID-19) pneumonia. PubMed. 7(2). 55–61. 29 indexed citations
4.
Zhang, Ting, et al.. (2020). Asiaticoside attenuates bleomycin-induced pulmonary fibrosis in A2aR−/− mice by promoting the BMP7/Smad1/5 signaling pathway. Biochemical and Biophysical Research Communications. 527(3). 662–667. 15 indexed citations
5.
Yang, Wenjie, Qiqi Cao, Le Qin, et al.. (2020). Clinical characteristics and imaging manifestations of the 2019 novel coronavirus disease (COVID-19):A multi-center study in Wenzhou city, Zhejiang, China. Journal of Infection. 80(4). 388–393. 681 indexed citations breakdown →
6.
Tan, Yiqing, Xiaoyang Wang, Wenjie Yang, et al.. (2020). COVID-19 patients with progressive and non-progressive CT manifestations. PubMed. 7(3). 97–105. 2 indexed citations
7.
Dong, Chen, Xiaokun Li, Qifa Song, et al.. (2020). Assessment of Hypokalemia and Clinical Characteristics in Patients With Coronavirus Disease 2019 in Wenzhou, China. JAMA Network Open. 3(6). e2011122–e2011122. 197 indexed citations
8.
Shao, Tuo, Tong Yu, Feifei Su, et al.. (2020). Gamma‐Glutamyltransferase Elevation Is Frequent in Patients With COVID‐19: A Clinical Epidemiologic Study. Hepatology Communications. 4(12). 1744–1750. 22 indexed citations
9.
Jiang, Xiangao, Megan Coffee, Anasse Bari, et al.. (2020). Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity. Computers, materials & continua/Computers, materials & continua (Print). 62(3). 537–551. 271 indexed citations
10.
Dai, Jianyi, et al.. (2015). Prevalence and types of drug-resistant variants in Chinese patients with acute hepatitis B. Journal of Medical Virology. 87(9). 1527–1531. 3 indexed citations
11.
Dai, Jianyi, et al.. (2004). [Genotyping of HBV DNA in Shenzhen and clinical manifestations].. PubMed. 12(4). 199–200. 2 indexed citations
12.
Dai, Jianyi, et al.. (2003). [Expression of P27 protein and cyclin E in colon cancer].. PubMed. 22(10). 1093–5. 3 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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