Yih Chung Tham

29.6k total citations · 4 hit papers
238 papers, 10.7k citations indexed

About

Yih Chung Tham is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Epidemiology. According to data from OpenAlex, Yih Chung Tham has authored 238 papers receiving a total of 10.7k indexed citations (citations by other indexed papers that have themselves been cited), including 177 papers in Radiology, Nuclear Medicine and Imaging, 162 papers in Ophthalmology and 37 papers in Epidemiology. Recurrent topics in Yih Chung Tham's work include Retinal Imaging and Analysis (132 papers), Glaucoma and retinal disorders (111 papers) and Retinal Diseases and Treatments (104 papers). Yih Chung Tham is often cited by papers focused on Retinal Imaging and Analysis (132 papers), Glaucoma and retinal disorders (111 papers) and Retinal Diseases and Treatments (104 papers). Yih Chung Tham collaborates with scholars based in Singapore, China and Hong Kong. Yih Chung Tham's co-authors include Tien Yin Wong, Ching‐Yu Cheng, Tin Aung, Li Xiang, Harry A. Quigley, Charumathi Sabanayagam, Daniel Shu Wei Ting, Tyler Hyungtaek Rim, Ya Xing Wang and Marco Yu and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Yih Chung Tham

216 papers receiving 10.5k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Global Prevalence of Glaucoma and Projections of Glaucoma Burden through 2040

2014 4.8k citations Yih Chung Tham, Tien Yin Wong et al. profile →
Global Prevalence of Diabetic Retinopathy and Projection of Burden through 2045

2021 1.2k citations Yih Chung Tham, Marco Yu et al. profile →
Logistic regression was as good as machine learning for predicting major chronic diseases

2020 339 citations Simon Nusinovici, Yih Chung Tham et al. profile →
Benchmarking large language models’ performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard

2023 202 citations Zhi Wei Lim, Samantha Min Er Yew et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yih Chung Tham Singapore	37	7.9k	6.1k	1.2k	1.0k	760	238	10.7k
Ya Xing Wang China	51	8.2k 1.0×	6.6k 1.1×	744 0.6×	601 0.6×	2.3k 3.0×	246	10.2k
Pearse A. Keane United Kingdom	58	8.7k 1.1×	8.1k 1.3×	846 0.7×	480 0.5×	614 0.8×	383	12.6k
Charumathi Sabanayagam Singapore	49	5.6k 0.7×	5.1k 0.8×	993 0.8×	834 0.8×	1.7k 2.3×	264	10.7k
Gavin Siew Wei Tan Singapore	37	4.6k 0.6×	4.4k 0.7×	893 0.7×	277 0.3×	449 0.6×	119	6.7k
Rajiv Raman India	34	4.5k 0.6×	5.6k 0.9×	402 0.3×	278 0.3×	695 0.9×	232	8.8k
Ningli Wang China	43	5.3k 0.7×	4.1k 0.7×	977 0.8×	781 0.7×	1.5k 2.0×	416	7.4k
Ching‐Yu Cheng Singapore	62	18.4k 2.3×	14.2k 2.3×	3.4k 2.8×	2.4k 2.3×	4.0k 5.3×	518	25.2k
Alicja R. Rudnicka United Kingdom	51	5.2k 0.7×	5.2k 0.9×	605 0.5×	1.6k 1.5×	1.7k 2.2×	183	11.0k
Mingguang He China	65	13.9k 1.8×	13.7k 2.2×	865 0.7×	1.6k 1.6×	8.3k 10.9×	647	19.2k
Neil M. Bressler United States	81	21.5k 2.7×	16.7k 2.7×	3.2k 2.6×	424 0.4×	1.8k 2.4×	291	24.0k

Countries citing papers authored by Yih Chung Tham

Since Specialization

Citations

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

Fields of papers citing papers by Yih Chung Tham

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yih Chung Tham. 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 Yih Chung Tham. The network helps show where Yih Chung Tham may publish in the future.

Co-authorship network of co-authors of Yih Chung Tham

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Luo, Xufei, et al.. (2025). Generative Artificial Intelligence Tools in Medical Research (GAMER): Protocol for a Scoping Review and Development of Reporting Guidelines. JMIR Research Protocols. 14. e64640–e64640.

Jiang, Nan, et al.. (2025). Digital Therapeutics in China: Comprehensive Review. Journal of Medical Internet Research. 27. e70955–e70955.

Liu, Xinyu, Samantha Min Er Yew, Bin Sheng, et al.. (2025). Can large language models fully automate or partially assist paper selection in systematic reviews?. British Journal of Ophthalmology. 109(8). 962–966. 5 indexed citations

Peng, Qingsheng, Tyler Hyungtaek Rim, Zhi Da Soh, et al.. (2025). Predictive Potential of Retina‐Based Biological Age in Assessing Chronic Obstructive Pulmonary Disease Risk. Clinical and Experimental Ophthalmology. 53(4). 402–408. 2 indexed citations

Feng, Xiaoru, Mingjie Luo, Qi He, et al.. (2024). Latest developments of generative artificial intelligence and applications in ophthalmology. Asia-Pacific Journal of Ophthalmology. 13(4). 100090–100090. 3 indexed citations

Ting, Daniel Shu Wei, Alfred Wei Chieh Kow, Fernando Bello, et al.. (2024). Medical education and physician training in the era of artificial intelligence. Singapore Medical Journal. 65(3). 159–166. 16 indexed citations

Cheong, Kai Xiong, Hengtong Li, Yih Chung Tham, et al.. (2023). Relationship Between Retinal Layer Thickness and Genetic Susceptibility to Age-Related Macular Degeneration in Asian Populations. SHILAP Revista de lepidopterología. 3(4). 100396–100396. 5 indexed citations

Rim, Tyler Hyungtaek, Sungha Park, Sung Soo Kim, et al.. (2023). Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores. European Heart Journal - Digital Health. 4(3). 236–244. 15 indexed citations

Wu, Liwei, Linlin Ren, Hanyun Liu, et al.. (2023). Letter 2 regarding “Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma”. Clinical and Molecular Hepatology. 30(1). 113–117. 3 indexed citations

10.

Soh, Zhi Da, Monisha E. Nongpiur, Marco Yu, et al.. (2023). Deep Learning-based Quantification of Anterior Segment OCT Parameters. SHILAP Revista de lepidopterología. 4(1). 100360–100360. 6 indexed citations

11.

Majithia, Shivani, Crystal Chun Yuen Chong, Miao Li Chee, et al.. (2023). Associations between Chronic Kidney Disease and Thinning of Neuroretinal Layers in Multiethnic Asian and White Populations. SHILAP Revista de lepidopterología. 4(1). 100353–100353. 4 indexed citations

12.

Cheung, Carol Y., Da‐Wei Li, Yih Chung Tham, et al.. (2023). AI-integrated ocular imaging for predicting cardiovascular disease: advancements and future outlook. Eye. 38(3). 464–472. 12 indexed citations

13.

Lee, Chan Joo, Tyler Hyungtaek Rim, Hyun Goo Kang, et al.. (2023). Pivotal trial of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from CMERC-HI. Journal of the American Medical Informatics Association. 31(1). 130–138. 18 indexed citations

14.

Gupta, Preeti, Ryan Eyn Kidd Man, Eva Fenwick, et al.. (2022). Associations between visual impairment, incident falls and fall frequency among older asians: longitudinal findings from the Singapore Epidemiology of Eye Diseases study. British Journal of Ophthalmology. 107(11). 1590–1596. 11 indexed citations

15.

Gunasekeran, Dinesh Visva, Yih Chung Tham, Daniel Shu Wei Ting, Gavin Siew Wei Tan, & Tien Yin Wong. (2021). Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology. The Lancet Digital Health. 3(2). e124–e134. 102 indexed citations

16.

Soh, Zhi Da, Miao Li Chee, Sahil Thakur, et al.. (2020). Asian‐specific vertical cup‐to‐disc ratio cut‐off for glaucoma screening: An evidence‐based recommendation from a multi‐ethnic Asian population. Clinical and Experimental Ophthalmology. 48(9). 1210–1218. 16 indexed citations

17.

Ran, An Ran, Clement C. Tham, Poemen P. Chan, et al.. (2020). Deep learning in glaucoma with optical coherence tomography: a review. Eye. 35(1). 188–201. 71 indexed citations

18.

Majithia, Shivani, Yih Chung Tham, Miao Li Chee, et al.. (2019). Singapore Chinese Eye Study: key findings from baseline examination and the rationale, methodology of the 6-year follow-up series. British Journal of Ophthalmology. 104(5). 610–615. 26 indexed citations

19.

Tham, Yih Chung, et al.. (2018). Blindness, low vision and cataract surgery outcome among adults in Hohhot of Inner Mongolia: a Rapid Assessment of Avoidable Blindness (RAAB) study. British Journal of Ophthalmology. 102(12). 1653–1657. 6 indexed citations

20.

Cheng, Ching‐Yu, Yih Chung Tham, Lingam Vijaya, et al.. (2017). Are Diabetes, Hypertension, and Obesity Associated with Primary Open Angle Glaucoma? A meta-analysis of 13 population-based studies in Asia. Investigative Ophthalmology & Visual Science. 58(8). 3712–3712.

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.

Explore authors with similar magnitude of impact