Krithi Pushpanathan
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Family Practice top 10%
Papers in ⓘ
-
- Artificial Intelligence in Healthcare and Education 5
- Co-authors
- Yih Chung Tham (9 shared papers)David Ziyou Chen (6 shared papers)Samantha Min Er Yew (4 shared papers)Jocelyn Hui Lin Goh (6 shared papers)Victor Koh (4 shared papers)Marcus Chun Jin Tan (3 shared papers)Zhi Wei Lim (2 shared papers)Bin Sheng (2 shared papers)
- Journals
- iScience (1 paper)BMJ Open Ophthalmology (1 paper)British Journal of Ophthalmology (1 paper)EBioMedicine (1 paper)Frontiers in Bioengineering and Biotechnology (1 paper)
- Partner nations
- SingaporeChinaUnited States
In The Last Decade
Krithi Pushpanathan
9 papers receiving 400 citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Health Informatics 217
- Family Practice 22
- Radiology, Nuclear Medicine and Imaging 148
- Health Information Management 21
- Ophthalmology 32
Countries citing papers authored by Krithi Pushpanathan
This map shows the geographic impact of Krithi Pushpanathan'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 Krithi Pushpanathan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Krithi Pushpanathan more than expected).
Fields of papers citing papers by Krithi Pushpanathan
This network shows the impact of papers produced by Krithi Pushpanathan. 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 Krithi Pushpanathan. The network helps show where Krithi Pushpanathan may publish in the future.
Co-authors
The 25 scholars most cited alongside Krithi Pushpanathan, 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 | Benchmarking large language models’ performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard Hit paper breakdown → | 2023 | 202 |
| 2 | 2023 | 51 | |
| 3 | 2024 | 38 | |
| 4 | 2022 | 32 | |
| 5 | 2021 | 31 | |
| 6 | 2021 | 24 | |
| 7 | 2023 | 21 | |
| 8 | 2025 | 3 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 0 | |
| 11 | 2025 | 0 | |
| 12 | 2025 | 0 |
About Krithi Pushpanathan
Krithi Pushpanathan is a scholar working on Health Informatics, Family Practice, Ophthalmology, Radiology, Nuclear Medicine and Imaging and Health Information Management, having authored 12 papers that have together received 403 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (6 papers), Artificial Intelligence in Healthcare and Education (5 papers), COVID-19 diagnosis using AI (3 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Retinal and Optic Conditions (3 papers), Plant biochemistry and biosynthesis (2 papers), Enzyme Catalysis and Immobilization (2 papers) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Health Informatics (217 citations), Family Practice (22 citations), Radiology, Nuclear Medicine and Imaging (148 citations), Health Information Management (21 citations) and Ophthalmology (32 citations). Krithi Pushpanathan has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include Yih Chung Tham, David Ziyou Chen, Samantha Min Er Yew, Jocelyn Hui Lin Goh, Victor Koh, Marcus Chun Jin Tan, Zhi Wei Lim, Bin Sheng, Chen‐Hsin Sun and Ching‐Yu Cheng. Their work appears in journals such as iScience, BMJ Open Ophthalmology, British Journal of Ophthalmology, EBioMedicine and Frontiers in Bioengineering and Biotechnology.
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.