Modern technology and artifacheel inteliations (AI) have given a new direction to the eye study, visual science. By analyzing retina images with the help of AI and Machine Learning ,, not only indicate a variety of people related to the eye diseases, but a clear part of the body. That is why it is considered a true witness of the nervous position of the body.
Down to the report published in Earth, the shrinking of small blood pressure in retina, while the wide of large veins can be attached to the problems of the large veins. In addition, the Arteryol-to-Venellor diameter ratio is a significant bioamar for stroke and heart disease. In such a situation, the regular retinal check helps to identify the risk of diabetes, kidney disease, heart problems and even neumlobal disorders.
For the past two decades, retinal immunition techniques like antique blood vessels such as photography, optical blood vessels, and optimal comments, and compatible opiography (oct-a), and compatible optics (oct-a), and compatible optics are easy to get high-resolution pictures such as eye-resolution. These techniques are used to check for diabetes ratinopathy, glaucoma and age-related macular degeneration. Now AI software can read these pictures and automatically analyze the exact status of the veins and arteries.
Recently, a technology named Oulumics has already designed to understand the Ratital Microvascular Biographers. AI is also prophesying from the pictures of first and after the pictures now and after the planning of the surgery and admonish the patient. In the country like India where the number of diabetes is increasing, the non-aggressive sugar screening can be very effective. While the current HBA1C test requires a blood samples, search teams are developing a deep training structure that can measure blood sugar levels (HBA1C using a picture of retina.
Another project is based on AC-Gan (Auxiliary Adparetors Generative Adware Nethers), which can detect a number of diseases at the same time from the retinal images. This can initially assess several problems like diabetes, heart and kidneys disease in a scan. However, there are challenges in this AI-based treatment.