Artificial Intelligence, a new hope for early diagnosis of cataracts

One of the most common eye diseases in the world is the cause of more than half of blindness and imposes multi -billion dollars annually on health systems.
The disease, which threatens the eye lens, has no obvious symptoms in the early stages and is often diagnosed when the patient’s vision has declined sharply.

According to the World Health Organization, millions of people around the world are dealing with the disease, but in low -income areas, access to screening and early diagnosis is still limited.

Recently, a study led by Maryam Karwashan from Fasa University of Medical Sciences, in collaboration with Kerman University of Medical Sciences, has shown that artificial intelligence can make a change in the diagnosis and management of cataracts. This study evaluates the efficiency of machine learning algorithms such as twisting neural networks, deep learning and decision tree by systematic review of scientific articles from Pubmed, Scopus and Web of Science.

The results indicate that these algorithms were effective in diagnosis, 2 % for management, and 2 % for the disease, and the torsional neural networks, especially in accurate diagnosis, have superior performance.

The findings of this study show that artificial intelligence not only increases the accuracy and speed of the diagnosis of cataracts, but can also fill the medical service gap in deprived areas.

Simple AI -based tools, such as mobile apps, can help personnel in remote areas to identify suspicious patients. This technology has the potential to become part of the health screening programs, especially in developing countries.

The article is published in the two months of “Health Meaning” at Tehran University of Medical Sciences and is an important step towards using new technologies to improve public health.