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Scans the demographic data of a given region and predicts the weights of these demographic factors (age, gender, economic background, location, etc) in a successful cataract surgery.

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Samsriddhi/Cataract-Modelling

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Cataract-Modelling

An AI model that scans the demographic data of a given region and predicts the weights of these demographic factors (age, gender, economic background, location, etc) in a successful cataract surgery. The data used is not made available to the public for it was used with a license.

Introduction:

The United Nations Development Programme’s Sustainable Development Goals were adopted as a part of the 2030 Agenda for Sustainable Development by the United Nations General Assembly. While there are 17 vast Sustainable Development Goals, these 17 address the key global challenges, including hunger, healthcare and well-being, education, and gender inequality.

Sustainable Development Goal 3, which is that of “Good Health and Well-being”, has an ultimate goal to ensure healthy lives and promote the well-being of all people irrespective of their age. To ensure this, proper healthcare systems must exist worldwide. However, even in the 21st century, women face multiple barriers towards gaining access to healthcare. Several studies conducted globally have documented disparities.

Cataract is one of the most common causes of visual impairment leading to blindness in older adults globally. As the world’s population ages, the prevalence of cataract too increases, and thus, cataract - its prevention, and proper treatment is a global challenge. One of the astonishing bits of evidence is that women have a higher prevalence of cataract than men, which essentially makes the case study of cataract a peculiar one when it comes to modelling healthcare systems. In India, studies suggest that females are less likely to have surgery for cataracts although the occurrence and the blindness burden is higher for women.

Results:

Less than half of the individuals with cataracts presented to the hospital for surgery. Among the patients who underwent treatment, there was an overall decrease in the number of blind individuals and visually impaired individuals. The barriers to cataract surgery were older age, greater distance to the hospital, municipalities with fewer inhabitants and less ophthalmic services.

In India, cataract is responsible for 66.2 % of blindness cases in people above 50, according to the National Blindness and Visual Impairment Survey. The condition behind these cases include 80.7 percent severe visual impairment cases and 70.2 percent moderate visual impairment cases in the age group.

Cost was the biggest barrier in accessing a cataract surgery. It was the reason for 22.1 percent blindness cases and lack of awareness was behind 18.4 percent cases, who did not feel any need of the surgery, according to the report. The World Vision Report released by the World Health Organization (WHO) on October 8, 2019 also pointed out that high costs involved in accessing eye care, especially for rural populations, was a major driver of visual impairment. It called for expansion of Universal Healthcare Coverage and including eye care services in it. Types of cataract surgeries and success rates: Phacoemulsification: best method but usually practiced in developed countries only, high cost Intracapsular Cataract Extraction: not in used in recent times after development of ECCE Extracapsular Cataract Extraction : success rate of 90-95% , most prevalent in developing countries, better success rate and effectiveness than MSICS Manual small incision cataract surgery (MSICS) - also common in developing countries with success rate slightly more than just 50% Comparison of the most used Cataract Surgical Methods - Both phacoemulsification and extracapsular cataract surgery achieve excellent visual outcomes with low complication rates. Though extracapsular cataract surgery is significantly faster, less expensive and requires less technology. Therefore, extracapsular cataract surgery is the preferred technique for cataract surgery in the developing world.

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Scans the demographic data of a given region and predicts the weights of these demographic factors (age, gender, economic background, location, etc) in a successful cataract surgery.

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