Prof Tien Yin Wong

Prof Tien Yin Wong

Professor of Medical AI and Ophthalmology

Position: Vice-Provost, Tsinghua University & Senior Vice-Chancellor, Tsinghua Medicine

Specialization: Artificial Intelligence in Ophthalmology, Diabetic Retinopathy, Medical Imaging

Affiliation: Tsinghua Medicine, Tsinghua University

Research Focus

Prof Tien Yin Wong is a world-renowned expert in ophthalmology and artificial intelligence applications in medicine. His research focuses on the development and validation of AI systems for eye disease detection and monitoring, particularly diabetic retinopathy. He has pioneered the integration of deep learning and medical imaging to improve primary healthcare outcomes.

Key Research Areas

  • AI-based detection of diabetic retinopathy and other eye diseases
  • Retinal imaging-based cardiovascular risk assessment
  • AI applications for Alzheimer's disease detection
  • Deep learning systems for chronic kidney disease screening
  • Teleophthalmology and AI-based screening programs

Selected Publications

  1. Li J, Guan Z, Wang J, Cheung CY, ..., Wong TY * . Integrated image-based deep learning and language models for primary diabetes care. Nat Med. 2024.
  2. Ma WZ, Sheng B, Yang L, ..., Wong TY* . Evolution of Future Medical AI Models – From Task-Specific, Disease-Centric to Universal Health. New England Journal of Medicine AI 2024.
  3. Dai L, Sheng B, Chen T, ..., Wong TY * . A deep learning system for predicting time to progression of diabetic retinopathy. Nat Med. 2023.
  4. Cheung CY, Ran AR, Wang S, ..., Wong TY * . A deep learning model for detection of Alzheimer's disease based on retinal photographs. Lancet Digit Health 2022.
  5. Cheung CY, Xu D, Cheng CY, ..., Wong TY * . A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre. Nat Biomed Eng 2020.

Notable Contributions

  • Development of AI systems for diabetic retinopathy screening across multiethnic populations
  • Creation of deep learning algorithms for chronic kidney disease detection from retinal photographs
  • Research on AI for early detection of Alzheimer's disease using retinal imaging
  • Establishment of international guidelines for diabetic eye care
  • Leadership in the integration of retinal imaging and AI for cardiovascular risk assessment