Optimizing dry eye disease diagnosis: integrating deep learning insights from OSDI questionnaires and ocular blinking videos

Author:

Wang Mini Han,Lin Zhiyuan,Zeng Peijin,Fang Xiaoxiao,Yu Yang,Hu Wenhan,Liu Yunxiao,Liu Haoyang,Li Xinyue,Jiang Xudong,Chen Guangshun,Zhou Ruoyu,Hou Guanghui,Chong Kelvin KL,Fang Junbin

Publisher

SPIE

Reference18 articles.

1. AI-based Advanced approaches and dry eye disease detection based on multisource evidence: Cases, applications, issues, and future directions;Wang;Big Data Mining and Analytics,2023

2. Ocular Surface Disease Index (OSDI) Versus the Standard Patient Evaluation of Eye Dryness (SPEED)

3. Impact of Incomplete Blinking Analyzed Using a Deep Learning Model With the Keratograph 5M in Dry Eye Disease

4. Can Explainable Artificial Intelligence Optimize the Data Quality of Machine Learning Model? Taking Meibomian Gland Dysfunction Detections as a Case Study;Wang,2023

5. A Review of Artificial Intelligence in Ophthalmology Field—Taking the Fundus Diagnosis Based on OCT Images as an Example

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