Glaucoma is an eye disease with high prevalence globally, and especially common among the elderly. However, due to the lack of early symptoms and long waiting hours in hospitals, patients are often not aware of this disease, causing them to miss the prime time of treating glaucoma. To help protect people’s eyesight from glaucoma, it is a must to speed up the diagnosis process of glaucoma without adding immense stress on the medical system. With this aim in mind, we have created OptiScan, an AI system that detects glaucoma by analysing retinal images, which can be used for glaucoma screening. OptiScan is trained in Colab, with Tensorflow and PyTorch as the dataset’s library. In a pre-trained ResNet-50 model, we imported a dataset containing 2333 images, which are retinal images of glaucoma patients and normal people. 80% of the dataset was used for training, while the remaining were used to validate the system. After validation, an accuracy of 88.2% was obtained. By using OptiScan as an early screening test to spot potential glaucoma patients before conducting time consuming eye check-ups, we can deal with the difficulties of glaucoma detection efficiently. Firstly, our test can be completed quickly as long as one has obtained their retinal image, therefore helping to raise the willingness of people to check their eye condition regularly. Secondly, as OptiScan doesn’t require professionals to analyse the retinal images, it is not affected by the shortage of medical resources, meaning that it can maintain fast and efficient screening at any time. Medicine resources can then be prioritised to people who have been tested as glaucoma patients, ensuring that the limited medical resources can be properly allocated according to people’s needs, so that patients can be diagnosed and receive treatment as soon as possible. With simple, fast operation steps and easily readable results with no complicated wordings, OptiScan is particularly useful for the elderly who may initially be unwilling to receive eye check-ups to avoid the hassle. Our system’s future potentials include converting it into a phone application, as well as inputting more types of datasets to train the system for more eye diseases. In the future when taking retinal images with phone camera has become more widely used, OptiScan can even be used at home, further improving its accessibility to allow everyone to use it conveniently.