School of Optometry 眼科視光學院
Home About Us What's New Subscribe eNewsletter Contact Us My School 繁體 简体 Text Only Print
About us
Message from Head of School
Vision & Mission
Our People
Academic Staff
Affiliate Faculty Members
Honorary & Adjunct Professor
Visiting Staff & Academic Visitors
Optometry Clinic Staff
Research Staff
Research Students
Our Research
About us > Our People > Research Students > Mr. Dong LIANG
Our People
Mr. Chunghim SO | Mr. Dong LIANG | Mr. Milan RAI | Ms. Jing ZHANG | Ms. Shuwen JIA | Ms. Wing Yan LAU | Ms. Yingkun CUI | Ms Jingfang Jennifer BIAN | Mr Shashi Kant CHAUDHARY | Ms Meng CHENG | Mr Ka Wai Jimmy CHEUNG | Ms Hang I Christie LAM | Ms Hoi Lam LI | Ms Sonal Aswin VYAS | Mr Kin Ken WAN | Ms Biyue GUO | Ms Li PAN | Ms Qi TAN | Mr Mezbah UDDIN | Ms Rong LI | Ms. Yuanyuan LIANG | Ms Anqi LYU | Mr Ying Hon SZE | Ms Qin WANG | Ms Hanyu ZHANG | Ms Wei YANG | Ms Mei ZHAO | Ms Yajing YANG | Ms Fangyu XU | Mr Sung Hei Jimmy TSE | Ms. Seen Hang CHAN | Mr. CHAN Kin Ho | Ms. AYERAKWAH Patience Ansomah | Mr. SO Ching | Mr. CATRAL Kirk Patrick Carreon | Mr. LIU Zhengji | Mr. LU Daqian | Ms. QIU Chunting | Mr. YANG Xiayin

Mr. Dong LIANG

Mr. Dong LIANG
PhD Student

ORCiD 0000-0003-4168-1140

Title of project:
Predicting myopia development based on machine learning

Synopsis:
Myopia is becoming a global public health problem due to its high prevalence rate and complex aetiology. Several studies showed that the development of myopia involves both genetic and environmental factors, and sometimes there may be relevant multiple structural and functional anomalies found in myopic eyes. Up to now, no prediction system has been widely accepted and validated for myopia development.

Machine learning methods build a mathematical model based on the large-scale training data, not by explicit rules but relying on inherent patterns instead, and make predictions in the testing data. Compared with statistical modelling, machine learning techniques can improve the predictive performance by using more flexible models, especially for the complex data with high dimensionality, non-linearity, and heterogeneity. Since the reasons leading to myopia are complicated and various factors might contribute to the myopia development, it is expected that the machine learning based method may have better performance, combining more complex variables and information.