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Medical Frontiers: AI Deep Learning Applications in Diagnosing Eye Diseases

 

The primary goal of scientific research in the medical field is to identify and develop effective means to detect diseases. Such is the case for eye diseases, of which about 80% are preventable and curable.Artificial intelligence has been instrumental in inspiring a lot of research activity, together with the support of tech companies similar to that of Virginia Beach IT services in facilitating the availability of hard data for use in these endeavors.

Here are a few groundbreaking examples.

AI-driven eye diagnosis as accurate as doctors:
An artificial intelligence (AI) machine-learning algorithms have been developed by researchers from Johns Hopkins University to diagnose age-related macular degeneration (AMD) as accurate as human doctors.They created a deep learning-based machine grading technique to automatically assess AMD from magnified images of the eye also known as fundus images.

The study started in 2015 and the researchers began looking into ways on how to automate AMD diagnosis. This resulted in the development of an AI machine using a non-invasive imaging technique that provides high-quality multiple images of the retina.These techniques were found to also diagnose other diseases of the retina such as diabetic retinopathy, and also have the potential to diagnose neurodegenerative and vascular disorders.

AI tech used for diabetes-related eye diseases:
Researchers from the Google Brain initiative have developed an intuitive and self-optimizing AI algorithm that can study large volumes of eye images to detect eye problems caused by diabetes such as diabetic retinopathy (DR) and diabetic macular edema (DME).

The deep learning tool was found to detect these conditions with a high degree of accuracy.The deep learning algorithm is developed from artificial intelligence (AI) platforms in which a neural network performs an evaluative task through repetition and self-correction processes.The AI algorithm was trained with 128,175 fundus images from various levels of diabetic retinal disease which is then graded to reveal the different severity stages.

“We feel that with this kind of technology, once it is fully deployed, there will be more people screened for this disease and decreased rates of uncontrolled diabetic vision loss and diabetic retinopathy,” the researchers said.However, more work is still needed before the algorithm would qualify for clinical use and trials but the end goal is to increase access to available therapies and reduce costs for the screening and treatment of these eye diseases.

With AI poised to provide additional advanced resources for other health conditions, it won’t be long before tech companies that provide IT consulting would soon be recognized for its valuable contributions in technology sharing and cross-border collaboration to start healing the world one disease at a time.…