Wong, Tien Yin

Outcomes of Eyes with Lesions Composed of >50% Blood in the Comparison of Age-Related Macular Degeneration Treatments Trials (CATT)

Altaweel, M. M., Daniel, E., Martin, D. F., Mittra, R. A., Grunwald, J. E., Lai, M. M., Melamud, A., Morse, L. S., Huang, J., Ferris, F. L., et al. (2015) · Ophthalmology

Retinal Diseases and TreatmentsRetinal Imaging and Analysis

Cited by 51

A multi-ancestry genome-wide study incorporating gene–smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure

Sung, Y. J., de las Fuentes, L., Winkler, T. W., Chasman, D. I., Bentley, A. R., Kraja, A. T., Ntalla, I., Warren, H. R., Guo, X., Schwander, K., et al. (2019) · Human Molecular Genetics

Genetic Associations and EpidemiologyBlood Pressure and Hypertension Studies

Cited by 43

Deep learning algorithms to detect diabetic kidney disease from retinal photographs in multiethnic populations with diabetes

Betzler, B. K., Chee, E. Y. L., He, F., Lim, C. C., Ho, J., Hamzah, H., Tan, N. C., Liew, G., McKay, G. J., Hogg, R. E., et al. (2023) · Journal of the American Medical Informatics Association

Retinal Imaging and AnalysisChronic Kidney Disease and Diabetes

Cited by 42

Use of artificial intelligence with retinal imaging in screening for diabetes-associated complications: systematic review

Yang, Q., Bee, Y. M., Lim, C. C., Sabanayagam, C., Yim-Lui Cheung, C., Wong, T. Y., Ting, D. S. W., Lim, L.-L., Li, H., He, M., et al. (2025) · eClinicalMedicine

Retinal Imaging and AnalysisArtificial Intelligence in Healthcare

Cited by 38

Sensitivity analysis in clinical trials: three criteria for a valid sensitivity analysis

Parpia, S., Morris, T. P., Phillips, M. R., Wykoff, C. C., Steel, D. H., Thabane, L., Bhandari, M., Chaudhary, V., for the Retina Evidence Trials InterNational Alliance (R.E.T.I.N.A.) Study Group, Sivaprasad, S., et al. (2022) · Eye

Statistical Methods in Clinical TrialsStatistical Methods and Bayesian Inference

Cited by 32

Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites

He, F., Ng Yin Ling, C., Nusinovici, S., Cheng, C.-Y., Wong, T. Y., Li, J., & Sabanayagam, C. (2024) · Journal of Medical Internet Research

Chronic Kidney Disease and DiabetesArtificial Intelligence in Healthcare

Cited by 29

Gene-based therapeutics for acquired retinal disease: opportunities and progress

Tan, T.-E., Fenner, B. J., Barathi, V. A., Tun, S. B. B., Wey, Y. S., Tsai, A. S. H., Su, X., Lee, S. Y., Cheung, C. M. G., Wong, T. Y., et al. (2021) · Frontiers in Genetics

Retinal Development and DisordersRetinal Diseases and Treatments

Cited by 26

Familial aggregation of age-related macular degeneration in the Utah population

Luo, L., Harmon, J., Yang, X., Chen, H., Patel, S., Mineau, G., Yang, Z., Constantine, R., Buehler, J., Kaminoh, Y., et al. (2008) · Vision Research

Retinal Diseases and TreatmentsGenetic Associations and Epidemiology

Cited by 26

Inter-relationship between visual symptoms, activity limitation and psychological functioning in patients with diabetic retinopathy

Fenwick, E. K., Cheng, G. H.-L., Man, R. E. K., Khadka, J., Rees, G., Wong, T. Y., Pesudovs, K., & Lamoureux, E. L. (2018) · British Journal of Ophthalmology

Retinal Diseases and TreatmentsOphthalmology and Visual Impairment Studies

Cited by 23

Beyond vision loss: the independent impact of diabetic retinopathy on vision-related quality of life in a Chinese Singaporean population

Fenwick, E. K., Man, R. E. K., Gan, A. T. L., Kumari, N., Wong, C., Aravindhan, A., Gupta, P., Wang, J. J., Mitchell, P., Wong, T. Y., et al. (2019) · British Journal of Ophthalmology

Retinal Diseases and TreatmentsOphthalmology and Visual Impairment Studies

Cited by 16

Have AI-Generated Texts from LLM Infiltrated the Realm of Scientific Writing? A Large-Scale Analysis of Preprint Platforms

Cheng, H., Sheng, B., Lee, A., Chaudary, V., Atanasov, A. G., Liu, N., Qiu, Y., Wong, T. Y., Tham, Y.-C., & Zheng, Y. (2024) · bioRxiv (Cold Spring Harbor Laboratory)

Academic integrity and plagiarismAcademic Publishing and Open Access

Cited by 15

Real-World Prospective Validation and Economic Evaluation of Deep Learning– Based Diabetic Retinopathy Detection From Fundus Photographs: A Systematic Review and Meta-analysis

Ran, A. R., Ding, J. L., Tang, Z., Lam, C., Nguyen, T. X., Zhou, J., Zhang, S., Fang, D., Yang, D., Ng, V., et al. (2026) · Diabetes Care

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 7