Michael K. Y. Hsin

1.2k total citations · 1 hit paper
8 papers, 699 citations indexed

About

Michael K. Y. Hsin is a scholar working on Biophysics, Infectious Diseases and Molecular Biology. According to data from OpenAlex, Michael K. Y. Hsin has authored 8 papers receiving a total of 699 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Biophysics, 2 papers in Infectious Diseases and 2 papers in Molecular Biology. Recurrent topics in Michael K. Y. Hsin's work include Cell Image Analysis Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Michael K. Y. Hsin is often cited by papers focused on Cell Image Analysis Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Michael K. Y. Hsin collaborates with scholars based in China and Hong Kong. Michael K. Y. Hsin's co-authors include Ko‐Yung Sit, Timmy Wing‐Kuk Au, Kenrie P. Y. Hui, John M. Nicholls, Leo L. M. Poon, Malik Peiris, Haogao Gu, Ka‐Chun Ng, Michael C. W. Chan and John Chi Wang Ho and has published in prestigious journals such as Nature, Thorax and Lab on a Chip.

In The Last Decade

Michael K. Y. Hsin

8 papers receiving 693 citations

Hit Papers

SARS-CoV-2 Omicron variant replication in human bronchus ... 2022 2026 2023 2024 2022 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael K. Y. Hsin China 6 488 139 91 86 69 8 699
Timo B. Trefzer Germany 6 728 1.5× 257 1.8× 88 1.0× 215 2.5× 47 0.7× 7 1.2k
Yen‐Ta Lu Taiwan 15 244 0.5× 115 0.8× 130 1.4× 47 0.5× 80 1.2× 40 698
Kangtai Liu China 6 636 1.3× 262 1.9× 137 1.5× 144 1.7× 24 0.3× 8 1.1k
Takahiko Koyama United States 6 467 1.0× 172 1.2× 30 0.3× 33 0.4× 29 0.4× 14 583
Simon J. L. Petitjean Belgium 7 352 0.7× 235 1.7× 61 0.7× 44 0.5× 62 0.9× 8 616
Tiffany Tang United States 10 707 1.4× 249 1.8× 85 0.9× 85 1.0× 41 0.6× 12 912
Qingrong Zhang China 9 308 0.6× 235 1.7× 53 0.6× 106 1.2× 60 0.9× 30 664
Jonasel Roque United States 4 711 1.5× 342 2.5× 159 1.7× 352 4.1× 19 0.3× 7 1.2k
Sujeet Kumar India 12 243 0.5× 212 1.5× 35 0.4× 66 0.8× 31 0.4× 58 644
Yaxin Dai China 13 472 1.0× 229 1.6× 31 0.3× 71 0.8× 64 0.9× 17 811

Countries citing papers authored by Michael K. Y. Hsin

Since Specialization
Citations

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

Fields of papers citing papers by Michael K. Y. Hsin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael K. Y. Hsin. 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 Michael K. Y. Hsin. The network helps show where Michael K. Y. Hsin may publish in the future.

Co-authorship network of co-authors of Michael K. Y. Hsin

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

All Works

8 of 8 papers shown
1.
Lee, Kelvin C. M., et al.. (2024). Information‐Distilled Generative Label‐Free Morphological Profiling Encodes Cellular Heterogeneity. Advanced Science. 11(29). e2307591–e2307591. 7 indexed citations
2.
Hui, Kenrie P. Y., John Chi Wang Ho, Man Chun Cheung, et al.. (2022). SARS-CoV-2 Omicron variant replication in human bronchus and lung ex vivo. Nature. 603(7902). 715–720. 496 indexed citations breakdown →
3.
Hui, Kenrie P. Y., Ka‐Chun Ng, Haogao Gu, et al.. (2022). Replication of SARS-CoV-2 Omicron BA.2 variant in ex vivo cultures of the human upper and lower respiratory tract. EBioMedicine. 83. 104232–104232. 57 indexed citations
4.
Zhang, Yan, Lei Kang, Weixing Dai, et al.. (2022). High‐Throughput, Label‐Free and Slide‐Free Histological Imaging by Computational Microscopy and Unsupervised Learning (Adv. Sci. 2/2022). Advanced Science. 9(2). 1 indexed citations
5.
Zhang, Yan, Weixing Dai, Xiufeng Li, et al.. (2021). High‐Throughput, Label‐Free and Slide‐Free Histological Imaging by Computational Microscopy and Unsupervised Learning. Advanced Science. 9(2). e2102358–e2102358. 28 indexed citations
6.
Hsin, Michael K. Y., et al.. (2021). FP12.04 Intelligent Label-Free Image-Based Profiling for Lung Cancer Cell Detection and Classification. Journal of Thoracic Oncology. 16(3). S218–S218. 1 indexed citations
7.
Lee, Kelvin C. M., Maolin Wang, Hayden Kwok‐Hay So, et al.. (2020). Deep-learning-assisted biophysical imaging cytometry at massive throughput delineates cell population heterogeneity. Lab on a Chip. 20(20). 3696–3708. 41 indexed citations
8.
Yuan, Huiling, et al.. (2010). 15-Lipoxygenases and its metabolites 15(S)-HETE and 13(S)-HODE in the development of non-small cell lung cancer. Thorax. 65(4). 321–326. 68 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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