| Benchmarking large language models’ performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard ZW Lim, K Pushpanathan, SME Yew, Y Lai, CH Sun, JSH Lam, DZ Chen, ... EBioMedicine 95, 2023 | 190 | 2023 |
| Popular large language model chatbots’ accuracy, comprehensiveness, and self-awareness in answering ocular symptom queries K Pushpanathan, ZW Lim, SME Yew, DZ Chen, HAHE Lin, JHL Goh, ... Iscience 26 (11), 2023 | 38 | 2023 |
| Metabolic engineering of microbes for monoterpenoid production K Zhu, J Kong, B Zhao, L Rong, S Liu, Z Lu, C Zhang, D Xiao, ... Biotechnology Advances 53, 107837, 2021 | 34 | 2021 |
| Engineering Yarrowia lipolytica to Produce Itaconic Acid From Waste Cooking Oil L Rong, L Miao, S Wang, Y Wang, S Liu, Z Lu, B Zhao, C Zhang, D Xiao, ... Frontiers in Bioengineering and Biotechnology 10, 888869, 2022 | 26 | 2022 |
| Enhanced limonene production by metabolically engineered Yarrowia lipolytica from cheap carbon sources S Li, L Rong, S Wang, S Liu, Z Lu, L Miao, B Zhao, C Zhang, D Xiao, ... Chemical Engineering Science 249, 117342, 2022 | 22 | 2022 |
| Artificial intelligence for diabetes care: current and future prospects B Sheng, K Pushpanathan, Z Guan, QH Lim, ZW Lim, SME Yew, JHL Goh, ... The Lancet Diabetes & Endocrinology 12 (8), 569-595, 2024 | 20 | 2024 |
| Review of emerging trends and projection of future developments in large language models research in ophthalmology M Wong, ZW Lim, K Pushpanathan, CY Cheung, YX Wang, D Chen, ... British Journal of Ophthalmology 108 (10), 1362-1370, 2024 | 16 | 2024 |
| Benchmarking large language models' performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard. EBioMedicine 95: 104770 ZW Lim, K Pushpanathan, SME Yew, Y Lai, CH Sun, JSH Lam, DZ Chen, ... | 16 | 2023 |
| Benchmarking large language models’ performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard, EBioMedicine 95 (2023) ZW Lim, K Pushpanathan, SME Yew, Y Lai, CH Sun, JSH Lam, DZ Chen, ... | 6 | 2023 |
| Are Traditional Deep Learning Model Approaches as Effective as a Retinal-Specific Foundation Model for Ocular and Systemic Disease Detection? SME Yew, X Lei, JHL Goh, Y Chen, S Srinivasan, M Chee, ... arXiv preprint arXiv:2501.12016, 2025 | | 2025 |
| Can OpenAI o1 Reason Well in Ophthalmology? A 6,990-Question Head-to-Head Evaluation Study S Srinivasan, X Ai, M Zou, K Zou, H Kim, TWS Lo, K Pushpanathan, ... arXiv preprint arXiv:2501.13949, 2025 | | 2025 |
| Deep Imbalanced Regression Model for Predicting Refractive Error from Retinal Photos SME Yew, X Lei, Y Chen, JHL Goh, K Pushpanathan, CC Xue, YX Wang, ... Ophthalmology Science, 100659, 2024 | | 2024 |
| Language Enhanced Model for Eye (LEME): An Open-Source Ophthalmology-Specific Large Language Model A Gilson, X Ai, Q Xie, S Srinivasan, K Pushpanathan, MB Singer, J Huang, ... arXiv preprint arXiv:2410.03740, 2024 | | 2024 |
| Can OpenAI o1's Enhanced Reasoning Capabilities Extend to Ophthalmology? A Benchmark Study Across Large Language Models and Text Generation Metrics S Srinivasan, X Ai, M Zou, K Zou, H Kim, TWS Lo, K Pushpanathan, ... | | |
