Cyril Tang

436 total citations
13 papers, 245 citations indexed

About

Cyril Tang is a scholar working on Radiology, Nuclear Medicine and Imaging, Organic Chemistry and Pharmacology. According to data from OpenAlex, Cyril Tang has authored 13 papers receiving a total of 245 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Organic Chemistry and 4 papers in Pharmacology. Recurrent topics in Cyril Tang's work include Radiomics and Machine Learning in Medical Imaging (5 papers), COVID-19 diagnosis using AI (4 papers) and Radiology practices and education (4 papers). Cyril Tang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), COVID-19 diagnosis using AI (4 papers) and Radiology practices and education (4 papers). Cyril Tang collaborates with scholars based in Australia, China and United States. Cyril Tang's co-authors include Catherine M Jones, Nazanin Esmaili, Quinlan D. Buchlak, Jarrel Seah, Henry Rapoport, Luke Oakden‐Rayner, Peter Brotchie, Hung N. Pham, Ben Hachey and Benjamin P. Johnston and has published in prestigious journals such as Journal of the American Chemical Society, BMJ Open and Planta Medica.

In The Last Decade

Cyril Tang

10 papers receiving 241 citations

Peers

Cyril Tang
Marc Landsman United States
Anglin Dent Canada
Yuanyuan Luo China
Jong Seok Ahn South Korea
Jean Feydy France
Giuseppina Iacoviello Italy
Yuguo Tang China
Zhiqian Yu United States
Arved Bischoff Germany
Marc Landsman United States
Cyril Tang
Citations per year, relative to Cyril Tang Cyril Tang (= 1×) peers Marc Landsman

Countries citing papers authored by Cyril Tang

Since Specialization
Citations

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

Fields of papers citing papers by Cyril Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cyril Tang

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

All Works

13 of 13 papers shown
1.
Lu, Zhiyi, et al.. (2025). Design, Synthesis, and Biological Evaluation of Novel 4-Chromanone-Derived Compounds Incorporating an Oxime Ether Moiety. Russian Journal of General Chemistry. 95(6). 1483–1493.
2.
3.
Milne, Michael, Quinlan D. Buchlak, Nazanin Esmaili, et al.. (2024). Applications and potential of machine, learning augmented chest X-ray interpretation in cardiology. Minerva Cardiology and Angiology. 73(1). 8–22.
4.
Li, Pei, et al.. (2024). Design, Synthesis, and Bioassay Evaluation of Novel 4-Chromanone-Derived Compounds Incorporating Acylhydrazone Moiety. Russian Journal of General Chemistry. 94(3). 729–736. 2 indexed citations
5.
Milne, Michael, Quinlan D. Buchlak, Jason Chiang, et al.. (2023). Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review. Diagnostics. 13(4). 743–743. 20 indexed citations
6.
Tang, Cyril, Jarrel Seah, Michael Milne, et al.. (2023). Analysis of Line and Tube Detection Performance of a Chest X-ray Deep Learning Model to Evaluate Hidden Stratification. Diagnostics. 13(14). 2317–2317. 4 indexed citations
7.
Jones, Catherine M, Michael Milne, Cyril Tang, et al.. (2021). Assessment of the effect of a comprehensive chest radiograph deep learning model on radiologist reports and patient outcomes: a real-world observational study. BMJ Open. 11(12). e052902–e052902. 28 indexed citations
8.
Seah, Jarrel, Cyril Tang, Quinlan D. Buchlak, et al.. (2021). Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study. The Lancet Digital Health. 3(8). e496–e506. 128 indexed citations
9.
Seah, Jarrel, Cyril Tang, Quinlan D. Buchlak, et al.. (2021). Do comprehensive deep learning algorithms suffer from hidden stratification? A retrospective study on pneumothorax detection in chest radiography. BMJ Open. 11(12). e053024–e053024. 9 indexed citations
10.
11.
Yu, Mingfeng, Joseph K. Wong, Cyril Tang, et al.. (2015). Efficient deprotection of F-BODIPY derivatives: removal of BF2 using Brønsted acids. Beilstein Journal of Organic Chemistry. 11. 37–41. 28 indexed citations
12.
Lin, Lie‐Chwen, et al.. (2007). Structures and bioactivity of alkaloids from Stemona. Planta Medica. 73(9). 1 indexed citations
13.
Tang, Cyril & Henry Rapoport. (1972). Total synthesis of (+-)-camptothecin. Journal of the American Chemical Society. 94(24). 8615–8616. 22 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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2026