Early detection of visual impairment iscrucial frequently missed in young children, who are capable of only limited cooperation with standard vision tests.
Recently, Chinese scientists(develop) a smartphone-based deep learning system for early detection of visual impairments in young children. was reported in the international science journal Nature Medicine last week, the research was conducted by a team (lead) by Lin Haotian, professor at the Zhongshan Ophthalmic Center of the Sun Yat-sen University.
The system is designed to induce a steady gaze in children by using cartoon-like video imagery. Cameras capture features of the subjects for (far) analysis, using deep-learning models. For capable of identifying 16 ophthalmic (disorder), suchas congenital cataracts, congenital ptosis and congenital glaucoma, the systemdelivers an average screening (accurate) of more than 85 percent,said the report.
In the study, more than 25 million frames of videos from 3,652 children were collected (base) on deep-learning software used in the Tianhe-2 super computing center in Guangzhou, Guangdong province. (consequent), the system has the potential to be used by healthcare professionals, parents and caregivers for identifying young children with visual impairments.
