Chao‐Hsiung Hsu

461 total citations
18 papers, 362 citations indexed

About

Chao‐Hsiung Hsu is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Chao‐Hsiung Hsu has authored 18 papers receiving a total of 362 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Biomedical Engineering. Recurrent topics in Chao‐Hsiung Hsu's work include Advanced MRI Techniques and Applications (6 papers), Nanoparticle-Based Drug Delivery (4 papers) and Characterization and Applications of Magnetic Nanoparticles (3 papers). Chao‐Hsiung Hsu is often cited by papers focused on Advanced MRI Techniques and Applications (6 papers), Nanoparticle-Based Drug Delivery (4 papers) and Characterization and Applications of Magnetic Nanoparticles (3 papers). Chao‐Hsiung Hsu collaborates with scholars based in Taiwan, United States and France. Chao‐Hsiung Hsu's co-authors include Yung‐Ya Lin, Lian‐Pin Hwang, Ying‐Chih Lin, Zhao Li, Pi‐Tai Chou, Fang-Chu Lin, Chung‐Hsuan Chen, Shu‐Yi Lin, Nai‐Ti Lin and Shern‐Long Lee and has published in prestigious journals such as Angewandte Chemie International Edition, Biomaterials and Magnetic Resonance in Medicine.

In The Last Decade

Chao‐Hsiung Hsu

16 papers receiving 361 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chao‐Hsiung Hsu Taiwan 9 153 149 117 94 90 18 362
Cartney E. Smith United States 12 131 0.9× 136 0.9× 84 0.7× 115 1.2× 105 1.2× 14 370
Todd O. Pangburn United States 9 165 1.1× 135 0.9× 170 1.5× 91 1.0× 99 1.1× 11 421
Jenny Brinkmann Netherlands 9 125 0.8× 164 1.1× 135 1.2× 62 0.7× 147 1.6× 10 413
Lise N. Feldborg Spain 9 189 1.2× 80 0.5× 165 1.4× 164 1.7× 120 1.3× 9 417
Yuhui Gong China 10 165 1.1× 113 0.8× 126 1.1× 83 0.9× 90 1.0× 16 391
William M. MacCuaig United States 9 112 0.7× 219 1.5× 87 0.7× 147 1.6× 36 0.4× 15 426
Meike Schinnerer Germany 10 243 1.6× 103 0.7× 224 1.9× 64 0.7× 132 1.5× 13 461
Ruth Donohue Ireland 10 155 1.0× 107 0.7× 318 2.7× 100 1.1× 138 1.5× 10 542
Gregory P. Robbins United States 8 101 0.7× 120 0.8× 120 1.0× 60 0.6× 98 1.1× 11 356
Sabine Gradmann Netherlands 6 125 0.8× 84 0.6× 219 1.9× 93 1.0× 68 0.8× 6 437

Countries citing papers authored by Chao‐Hsiung Hsu

Since Specialization
Citations

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

Fields of papers citing papers by Chao‐Hsiung Hsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chao‐Hsiung Hsu. 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 Chao‐Hsiung Hsu. The network helps show where Chao‐Hsiung Hsu may publish in the future.

Co-authorship network of co-authors of Chao‐Hsiung Hsu

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

All Works

18 of 18 papers shown
1.
Hsu, Chao‐Hsiung, Bo Chang, Mark Burke, et al.. (2025). StainAI: quantitative mapping of stained microglia and insights into brain-wide neuroinflammation and therapeutic effects in cardiac arrest. Communications Biology. 8(1). 462–462.
2.
Maeda, Takuya, Soichiro Henmi, Fahad Somaa, et al.. (2023). Mesenchymal Stromal Cell Delivery Via Cardiopulmonary Bypass Provides Neuroprotection in a Juvenile Porcine Model. JACC Basic to Translational Science. 8(12). 1521–1535. 2 indexed citations
3.
Kim, Ryan, Chao‐Hsiung Hsu, Scott Love, et al.. (2022). A Baboon Brain Atlas for Magnetic Resonance Imaging and Positron Emission Tomography Image Analysis. Frontiers in Neuroanatomy. 15. 778769–778769. 3 indexed citations
4.
Maeda, Takuya, Alice P. Chen, Chao‐Hsiung Hsu, et al.. (2022). Dose Effect of Mesenchymal Stromal Cell Delivery Through Cardiopulmonary Bypass. The Annals of Thoracic Surgery. 116(6). 1337–1345. 3 indexed citations
5.
Hsu, Chao‐Hsiung, et al.. (2022). Classification of Activated Microglia by Convolutional Neural Networks. PubMed. 2022. 198–202. 1 indexed citations
6.
Hsu, Chao‐Hsiung, Stephen Lin, Ai‐Chen Ho, et al.. (2020). Comparison of in vivo and in situ detection of hippocampal metabolites in mouse brain using 1H‐MRS. NMR in Biomedicine. 34(2). e4451–e4451. 10 indexed citations
7.
Li, Zhao, Chao‐Hsiung Hsu, Lian‐Pin Hwang, et al.. (2018). Dendrimer- and copolymer-based nanoparticles for magnetic resonance cancer theranostics. Theranostics. 8(22). 6322–6349. 73 indexed citations
8.
Lin, Fang-Chu, Chao‐Hsiung Hsu, & Yung‐Ya Lin. (2018). Nano-therapeutic cancer immunotherapy using hyperthermia-induced heat shock proteins: insights from mathematical modeling. International Journal of Nanomedicine. Volume 13. 3529–3539. 29 indexed citations
9.
Wang, Chencai, Chao‐Hsiung Hsu, Zhao Li, et al.. (2017). Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia. International Journal of Nanomedicine. Volume 12. 6273–6287. 38 indexed citations
10.
Zhao, Li, et al.. (2015). Sensitive imaging of magnetic nanoparticles for cancer detection by active feedback MR. Magnetic Resonance in Medicine. 74(1). 2 indexed citations
11.
Yao, Jingwen, Chao‐Hsiung Hsu, Zhao Li, et al.. (2015). Magnetic Resonance Nano-Theranostics for Glioblastoma Multiforme. Current Pharmaceutical Design. 21(36). 5256–5266. 16 indexed citations
12.
Zhao, Li, et al.. (2015). Sensitive imaging of magnetic nanoparticles for cancer detection by active feedback MR. Magnetic Resonance in Medicine. 74(1). 33–41. 5 indexed citations
13.
Ho, Lin‐Chen, Chao‐Hsiung Hsu, Chung‐Mao Ou, et al.. (2014). Unibody core–shell smart polymer as a theranostic nanoparticle for drug delivery and MR imaging. Biomaterials. 37. 436–446. 25 indexed citations
14.
Chen, Yu‐Wen, Chao‐Hsiung Hsu, & Dennis W. Hwang. (2014). Novel MRI contrast development by lock-in suppression. Magnetic Resonance in Medicine. 71(5). 1676–1681.
15.
Chen, Jyh‐Horng, et al.. (2011). Simple mobile single-sided NMR apparatus with a relatively homogeneous B0 distribution. Magnetic Resonance Imaging. 29(6). 869–876. 3 indexed citations
16.
Chen, Kuan‐Ju, Hao Wang, Chao‐Hsiung Hsu, et al.. (2010). A small MRI contrast agent library of gadolinium(III)-encapsulated supramolecular nanoparticles for improved relaxivity and sensitivity. Biomaterials. 32(8). 2160–2165. 77 indexed citations
17.
Lin, Nai‐Ti, Shu‐Yi Lin, Shern‐Long Lee, et al.. (2007). From Polynorbornene to the Complementary Polynorbornene by Replication. Angewandte Chemie International Edition. 46(24). 4481–4485. 65 indexed citations
18.
Lin, Nai‐Ti, Shu‐Yi Lin, Shern‐Long Lee, et al.. (2007). From Polynorbornene to the Complementary Polynorbornene by Replication. Angewandte Chemie. 119(24). 4565–4569. 10 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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