Mong Li Lee
- Ophthalmology top 0.2%
- Retinal Diseases and Treatments 27
- Glaucoma and retinal disorders 18
- Retinal and Optic Conditions 17
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- Retinal Imaging and Analysis 61
- Health Informatics top 1%
- Signal Processing top 1%
- Data Management and Algorithms 56
- Health Information Management top 0.5%
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- Advanced Database Systems and Queries 53
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- Data Mining Algorithms and Applications 31
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- Semantic Web and Ontologies 28
Mong Li Lee
218 papers receiving 5.5k citations
Hit Papers
Peers
Comparison fields: 5 of 174
- Ophthalmology 2.1k
- Radiology, Nuclear Medicine and Imaging 2.5k
- Health Informatics 133
- Signal Processing 748
- Health Information Management 282
Countries citing papers authored by Mong Li Lee
This map shows the geographic impact of Mong Li Lee'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 Mong Li Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mong Li Lee more than expected).
Fields of papers citing papers by Mong Li Lee
This network shows the impact of papers produced by Mong Li Lee. 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 Mong Li Lee. The network helps show where Mong Li Lee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mong Li Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 10 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 7 | |
| 6 | 2024 | 6 | |
| 7 | 2024 | 2 | |
| 8 | 2023 | 3 | |
| 9 | 2023 | 14 | |
| 10 | 2022 | 3 | |
| 11 | 2022 | 11 | |
| 12 | 2022 | 26 | |
| 13 | 2021 | 9 | |
| 14 | 2021 | 12 | |
| 15 | Effect of Image Compression and Number of Fields on a Deep Learning System for Detection of Diabetic Retinopathy | 2019 | 1 |
| 16 | 2018 | 10 | |
| 17 | Transformed Representations for Convolutional Neural Networks in Diabetic Retinopathy Screening | 2014 | 28 |
| 18 | 2012 | 2 | |
| 19 | Image mining: issues, frameworks and techniques | 2001 | 43 |
| 20 | ICICLES: Self-Tuning Samples for Approximate Query Answering | 2000 | 75 |
About Mong Li Lee
Mong Li Lee is a scholar working on Signal Processing, Ophthalmology, Health Information Management, Radiology, Nuclear Medicine and Imaging and Computer Networks and Communications, having authored 232 papers that have together received 5.8k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (61 papers), Data Management and Algorithms (56 papers), Advanced Database Systems and Queries (53 papers), Data Mining Algorithms and Applications (31 papers), Semantic Web and Ontologies (28 papers), Retinal Diseases and Treatments (27 papers), Glaucoma and retinal disorders (18 papers) and Retinal and Optic Conditions (17 papers). The work is most often cited by research in Ophthalmology (2.1k citations), Radiology, Nuclear Medicine and Imaging (2.5k citations), Health Informatics (133 citations), Signal Processing (748 citations) and Health Information Management (282 citations). Mong Li Lee has collaborated with scholars based in Singapore, United States and China. Frequent co-authors include Wynne Hsu, Tien Yin Wong, Gilbert Lim, Qiangfeng Peter Lau, Y. Li, Jie Jin Wang, Carol Y. Cheung, Tok Wang Ling, Paul Mitchell and Christopher A. Schuh. Their work appears in journals such as Investigative Ophthalmology & Visual Science, Scientific Reports, npj Digital Medicine, Journal of Intelligent Information Systems and The Lancet Digital Health.
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.