Ting Huang

2.7k total citations
150 papers, 1.9k citations indexed

About

Ting Huang is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Ophthalmology. According to data from OpenAlex, Ting Huang has authored 150 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Radiology, Nuclear Medicine and Imaging, 29 papers in Surgery and 25 papers in Ophthalmology. Recurrent topics in Ting Huang's work include Corneal surgery and disorders (28 papers), Corneal Surgery and Treatments (28 papers) and Glaucoma and retinal disorders (19 papers). Ting Huang is often cited by papers focused on Corneal surgery and disorders (28 papers), Corneal Surgery and Treatments (28 papers) and Glaucoma and retinal disorders (19 papers). Ting Huang collaborates with scholars based in China, Taiwan and United States. Ting Huang's co-authors include Yu‐Chiau Shyu, Yu‐Hsien Chen, Pei‐Jer Chen, Huang-Yang Chen, Chi‐Chin Sun, Fang‐Ping Chen, Chen Ouyang, Chao Hou, Paul Jen‐Hwa Hu and An‐Shine Chao and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and PLoS ONE.

In The Last Decade

Ting Huang

139 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ting Huang China 24 409 332 299 255 201 150 1.9k
Timur Köse Türkiye 30 317 0.8× 143 0.4× 205 0.7× 197 0.8× 109 0.5× 145 2.7k
Pei‐Kwei Tsay Taiwan 27 577 1.4× 258 0.8× 512 1.7× 189 0.7× 258 1.3× 103 2.8k
Cemil Çolak Türkiye 28 710 1.7× 289 0.9× 278 0.9× 241 0.9× 67 0.3× 264 3.0k
Aniello Maiese Italy 21 213 0.5× 180 0.5× 198 0.7× 330 1.3× 62 0.3× 118 1.8k
Jingjing Chen China 26 518 1.3× 542 1.6× 1.1k 3.7× 371 1.5× 442 2.2× 191 3.1k
David Hughes United Kingdom 28 722 1.8× 230 0.7× 321 1.1× 354 1.4× 150 0.7× 133 2.6k
Manpreet Kaur India 21 420 1.0× 496 1.5× 331 1.1× 87 0.3× 423 2.1× 220 2.0k
Huiying Liang China 25 323 0.8× 328 1.0× 370 1.2× 408 1.6× 44 0.2× 123 3.0k
Koichi Yamaguchi Japan 25 371 0.9× 412 1.2× 289 1.0× 166 0.7× 66 0.3× 114 2.9k
Diego Faggian Italy 25 304 0.7× 145 0.4× 431 1.4× 238 0.9× 44 0.2× 108 2.2k

Countries citing papers authored by Ting Huang

Since Specialization
Citations

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

Fields of papers citing papers by Ting Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting Huang

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

All Works

20 of 20 papers shown
1.
Ye, Weiyu, et al.. (2025). Exploring the dynamic responses of group 3 innate lymphoid cells at different times in response to LPS challenge. International Immunopharmacology. 148. 114162–114162. 1 indexed citations
2.
3.
Hu, Paul Jen‐Hwa, et al.. (2025). Predicting Metabolic Dysfunction–Associated Fatty Liver Disease Phenotypes Among Adults: 2-Stage Contrastive Learning Method. JMIR Medical Informatics. 13. e75747–e75747.
4.
Fan, Yangyang, Zhiyong Li, Xinyu Yang, et al.. (2025). Self-sustained Bio-Fenton system driven by Shewanella oneidensis for efficient degradation of persistent organic pollutants under oxygen-limited conditions. Journal of Hazardous Materials. 499. 140087–140087. 1 indexed citations
5.
Hu, Paul Jen‐Hwa, et al.. (2024). A meta-path, attention-based deep learning method to support hepatitis carcinoma predictions for improved cirrhosis patient management. Decision Support Systems. 181. 114226–114226. 1 indexed citations
6.
7.
Peng, Meixi, Zhenyu Wang, Yongxiu Huang, et al.. (2024). A novel LGALS1-depended and immune-associated fatty acid metabolism risk model in acute myeloid leukemia stem cells. Cell Death and Disease. 15(7). 482–482. 7 indexed citations
8.
Zhang, Haitao, Jinfeng Cai, Chunna Li, et al.. (2023). Wogonin inhibits latent HIV-1 reactivation by downregulating histone crotonylation. Phytomedicine. 116. 154855–154855. 17 indexed citations
9.
Hu, Paul Jen‐Hwa, et al.. (2023). A hierarchical multilabel graph attention network method to predict the deterioration paths of chronic hepatitis B patients. Journal of the American Medical Informatics Association. 30(5). 846–858. 2 indexed citations
10.
Zheng, Xiaomei, et al.. (2023). Exosomal circKIAA1797 Regulates Cell Progression and Glycolysis by Targeting miR-4429/PBX3 Pathway in Gastric Cancer. Biochemical Genetics. 62(3). 1762–1778. 2 indexed citations
11.
Huang, Ting, Jinfeng Cai, Peipei Wang, et al.. (2023). Ponatinib Represses Latent HIV-1 by Inhibiting AKT-mTOR. Antimicrobial Agents and Chemotherapy. 67(6). e0006723–e0006723. 8 indexed citations
12.
Wang, Chih‐Yuan, Yu‐Hsien Chen, & Ting Huang. (2022). Reduced-port robotic radical gastrectomy for gastric cancer: a single-institute experience. BMC Surgery. 22(1). 198–198. 6 indexed citations
13.
Sun, Chi‐Chin, Ting Huang, Tsai‐Sheng Fu, et al.. (2020). Association of age-related macular degeneration on fracture risks among osteoporosis population: a nationwide population-based cohort study. BMJ Open. 10(9). e037028–e037028. 7 indexed citations
14.
Hu, Paul Jen‐Hwa, et al.. (2020). A Deep Learning–Based Unsupervised Method to Impute Missing Values in Patient Records for Improved Management of Cardiovascular Patients. IEEE Journal of Biomedical and Health Informatics. 25(6). 2260–2272. 20 indexed citations
15.
Hu, Paul Jen‐Hwa, et al.. (2020). Predictive Analytics for Care and Management of Patients With Acute Diseases: Deep Learning–Based Method to Predict Crucial Complication Phenotypes. Journal of Medical Internet Research. 23(2). e18372–e18372. 17 indexed citations
16.
Shyu, Yu‐Chiau, Ting Huang, Cheng‐Hung Chien, et al.. (2019). Diabetes poses a higher risk of hepatocellular carcinoma and mortality in patients with chronic hepatitis B: A population‐based cohort study. Journal of Viral Hepatitis. 26(6). 718–726. 28 indexed citations
17.
Wu, Qianni, et al.. (2017). The ROCK inhibitor, thiazovivin, inhibits human corneal endothelial-to-mesenchymal transition/epithelial-to-mesenchymal transition and increases ionic transporter expression. International Journal of Molecular Medicine. 40(4). 1009–1018. 24 indexed citations
18.
19.
Yuan, Jin, et al.. (2012). Individual lamellar keratoplasty for Mooren's ulcer. Chinese Journal of Optometry & Ophthalmology. 14(8). 462–466. 1 indexed citations
20.
Blostein, Steven D. & Ting Huang. (1988). Correction to Error Analysis in Stereo Determination of 3-D Point Positions. IEEE Transactions on Pattern Analysis and Machine Intelligence. 10(5). 765. 20 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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