Development and Evaluation of Aeyeconsult: A Novel Ophthalmology Chatbot Leveraging Verified Textbook Knowledge and GPT-4.

Objective: There has been much excitement on the use of large language models (LLMs) such as ChatGPT in ophthalmology. However, LLMs are limited in that they are trained on unverified information and do not cite their sources. This paper highlights a new methodology to create a generative AI chatbot to answer eye care related questions which uses only verified ophthalmology textbooks as data and cites its sources.

Abnormal retinal capillary blood flow in autosomal dominant Alzheimer's disease.

Introduction: This study characterizes retinal capillary blood flow in subjects with autosomal dominant Alzheimer's disease (ADAD)-causing mutations.

Methods: Carriers of or mutations were prospectively recruited and split into early-stage (ES) and late-stage (LS) groups. Controls were normal subjects and non-carriers from the at-risk group.

Past, present and future role of retinal imaging in neurodegenerative disease.

Retinal imaging technology is rapidly advancing and can provide ever-increasing amounts of information about the structure, function and molecular composition of retinal tissue in humans in vivo. Most importantly, this information can be obtained rapidly, non-invasively and in many cases using Food and Drug Administration-approved devices that are commercially available. Technologies such as optical coherence tomography have dramatically changed our understanding of retinal disease and in many cases have significantly improved their clinical management.