Zhuoling Lin

TL;DR: It is shown that an AI agent using deep learning, and involving convolutional neural networks for diagnostics, risk stratification and treatment suggestions, accurately diagnoses and provides treatment decisions for congenital cataracts in an in silico test, a website-based study, in a ‘finding a needle in a haystack’ test and in a multihospital clinical trial.

TL;DR: CC-Cruisers exhibited less accurate performance comparing to senior consultants in diagnosing childhood cataracts and making treatment decisions, however, the medical service provided by CC-Cruiser was less time-consuming and achieved a high level of patient satisfaction.

TL;DR: The SMS reminders significantly improved follow-up adherence in pediatric cataract treatment and using readily available mobile phone resources may be an effective and economic strategy to improve management of Childhood Cataract in China.

TL;DR: A computer vision-based framework for the automatic localization and diagnosis of slit-lamp images by identifying the lens region of interest (ROI) and employing a deep learning convolutional neural network (CNN).

TL;DR: Age and sex were the most consistent predictors of ocular biometry in the older population from South China, providing normative values for AL, ACD, and K using the IOL Master for a population in South China.