The State-of-Art Deep Learning Technology in Ophthalmology (Ongoing)

Posted On 2019-06-13 17:18:01

This focused issue on “The State-of-Art Deep Learning Technology in Ophthalmology” is edited by Dr. Daniel Ting, from Singapore Eye Research Institute, National University of Singapore, Singapore and Dr. Haotian Lin, State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, China.

Dr. Daniel Ting graduated as the SingHealth Residency Valedictorian in 2016, then started his vitreo-fellowship training as an Associate Consultant in the Singapore National Eye Centre. In 2017, he was chosen to be the 2017 US-ASEAN Fulbright Scholar, representing Singapore to visit Johns Hopkins University School of Medicine and Applied Physics Laboratory to deepen his understanding on the use of artificial intelligence, big data analytics and telemedicine in the field of Ophthalmology.

Dr. Haotian Lin received his medical doctor degree from Sun Yat-Sen University and has devoted his efforts to a career in ophthalmological research for more than 10 years. He built the first cloud platform of intelligent diagnosis and treatment of cataract in the world, and is the creator of the world’s first intelligently ophthalmic clinic in Guangzhou, which was selected as one of "the 11 major AI events affecting the global medical community" by IEEE Spectrum and was the only selected one completed by a Chinese team.

Focused issue outline:

  1. Artificial Intelligence, Machine Learning and Deep Learning Made Easy
  2. AI Screening for anterior segment diseases
  3. AI Screening for diabetic retinopathy using fundus photographs
  4. AI Screening for glaucoma using fundus photographs
  5. AI Screening for age-related macular degeneration using fundus photographs
  6. AI Screening for Retinal Diseases using Optical Coherence Tomography
  7. AI Screening for Glaucoma using Optical Coherence Tomography
  8. AI Screening for Glaucoma using Humphrey Visual Field
  9. AI Screening for Retinal Vascular Diseases using fundus photographs
  10. AI Screening for Coronary Artery Diseases using fundus photographs
  11. The Input for Artificial Intelligence Screening of Retinal Images: Mobile and Fixed-location Imaging with Ultra-widefield Fundus Camera
  12. Glaucoma Screening from Color Fundus Images
  13. Optical Coherence Tomography and Artificial Intelligence for Glaucomatous Optic Neuropathy
  14. New Technologies for Retina Implant Based on Micro/Nano Engineering
  15. Retinal Degeneration Model in Mid to Large Size Animal and Retinal Prosthesis Development
  16. Design of a Novel Electrical Stimulation Scheme for Artificial Retina Combined with Biotechnology

The series “The State-of-Art Deep Learning Technology in Ophthalmology” was commissioned by the editorial office, Annals of Eye Science without any sponsorship or funding. Daniel Ting and Haotian Lin are serving as the unpaid Guest Editors for the series.