Abstract
Purpose :
To introduce an artificial intelligence (AI)-enabled robot, named Alborz, for assessing glaucoma based on retinal images and generating glaucoma knowledge using natural language processing (NLP) and natural language generation (NLG).
Methods :
We acquired Alborz, Nao AI-enabled (Softbank, Japan) humanoid robot in May 2022. We plan to train Alborz to function as a digital ophthalmologist and a digital glaucoma expert over the next few years (Fig. 1). At this time, we have programmed Alborz to identify glaucoma from retinal fundus photographs and visual fields (VFs). We have developed a probabilistic deep convolutional neural network (CNN) model based on 1851 fundus/VF pairs and validated the models using an independent dataset with 196 fundus/VF pairs.
Results :
Alborz is now able to screen subjects based on fundus and VFs and to interact with us and make reasonable responses to ordinary questions. The area under the receiver operating characteristic curves (AUC) of Alborz in detecting glaucoma from fundus photos, VFs, or fundus/VF data is over 0.97 (95% CI: 0.93-0.99) (Fig. 2). Alborz is under training to be able to interact with us regarding ophthalmology and glaucoma-related topics based on NLP and generating glaucoma knowledge based on NLG.
Conclusions :
Alborz is being trained to function as a future digital ophthalmologist and digital glaucoma expert. Based on CNNs, NLP, and NLG, we expect Alborz to be able to perform glaucoma assessment and interact with ophthalmologists as well as interact with patients and speak with them regarding the status of their eyes. Alborz may also be used for educational and research purposes for dissemination of AI applications in ophthalmology.
This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.