Year of graduation: 2013

Supervisors: Prof Christopher Kai Shun LEUNG

Research Direction

  • Medical Statistics
  • Image Analysis
  • Spatial Statistics
  • Machine Learning
  • Deep Learning
  • Artificial Intelligence

Current Affiliations and Positions

  • Senior Biostatisician, Singapore Eye Research Institute, Singapore

Representative Publications

  1. Lam, A. K. N., To, E., Weinreb, R. N., Yu, M., Mak, H., Lai, G., Chiu, V., Wu, K., Zhang, X., Cheng, T. P. H., Guo, P. Y., & Leung, C. K. S. (2020). Use of Virtual Reality Simulation to Identify Vision-Related Disability in Patients With Glaucoma. JAMA Ophthalmology, 138(5), 490–498.
  2. Nusinovici, S., Tham, Y. C., Chak Yan, M. Y., Wei Ting, D. S., Li, J., Sabanayagam, C., Wong, T. Y., & Cheng, C.-Y. (2020). Logistic regression was as good as machine learning for predicting major chronic diseases. Journal of Clinical Epidemiology, 122, 56–69.
  3. Yu, M., Tham, Y.-C., Rim, T. H., Ting, D. S. W., Wong, T. Y., & Cheng, C.-Y. (2019). Reporting on deep learning algorithms in health care. The Lancet Digital Health, 1(7), e328–e329.
  4. Yu, M., Lin, C., Weinreb, R. N., Lai, G., Chiu, V., & Leung, C. K.-S. (2016). Risk of Visual Field Progression in Glaucoma Patients with Progressive Retinal Nerve Fiber Layer Thinning: A 5-Year Prospective Study. Ophthalmology, 123(6), 1201–1210.
  5. Liu, S., Yu, M., Weinreb, R. N., Lai, G., Lam, D. S.-C., & Leung, C. K.-S. (2014) A Prospective Study of Frequency Doubling Technology Perimetry for Detection of Glaucoma Progression – A Linear Pointwise Regression Analysis. Investigative ophthalmology & visual science, 55(5), 2862-2869.
  6. Liu, S., Yu, M., Weinreb, R. N., Lai, G., Lam, D. S.-C., & Leung, C. K.-S. (2014). Frequency-Doubling Technology Perimetry for Detection of the Development of Visual Field Defects in Glaucoma Suspect Eyes: A Prospective Study. JAMA ophthalmology, 132(1), 77-83.
  7. Leung C. K., Yu, M., Lam D. S. (2013). “Detection of Disease-related Retinal Nerve Fiber Layer Thinning,” S. Patent Application No. 13/898,176 , Publication No. US20130308824 A1. Washington, DC: U.S.