A Multimodal Approach for Glaucoma Diagnosis and Classification

However, the lack of fully annotated medical datasets poses a challenge in applying CNNs to glaucoma diagnosis. To address these issues, a new multimodal dataset for glaucoma is introduced in this study. With the help of medical images, deep learning has shown great potential in the field of glaucoma diagnosis. By combining patient metadata, glaucoma segmentation, and medical image processing, the GMNNnet model provides a comprehensive and accurate diagnosis of glaucoma. In summary, this study presents a novel multimodal approach for glaucoma diagnosis and classification.