AI Intervention Options For Diabetic Retinopathy

  • Diabetic retinopathy could develop into an even more serious health catastrophe in the years to come.
  • The most common cause of vision impairment in adult populations worldwide is diabetic retinopathy.

There is a growing fear that diabetic retinopathy could develop into an even more serious health catastrophe in the years to come given that the International Diabetes Foundation predicts that at least 700 million people will have diabetes mellitus by 2045.

According to reports, diabetic retinopathy is the most common cause of vision impairment in adult populations worldwide. According to current statistics, more than one-third of diabetic patients may develop diabetic retinopathy.

According to a recent study, diabetic retinopathy affects 16.9% of people in India. As a result, more cutting-edge methods of preventing and treating diabetic retinopathy are required. One possibility is to use artificial intelligence (AI) to improve eye care for diabetic retinopathy patients.

To address diabetic patients’ eye problems, artificial intelligence employs machine learning and deep learning. This game-changing discovery has the potential to significantly improve diabetes management.

transforming diabetic retinopathy medical treatment

AI is transforming diabetic eye care in a variety of ways. Deep learning has been used to help medical professionals improve the efficiency of screening and diagnosing diabetic retinopathy at a low cost. Using convolutional neural networks, doctors can efficiently identify and track the progression of diabetic retinopathy using AI-based screening tools. This screening, which has an accuracy rate of 92%, is used to locate and diagnose potential retinal problems.

Furthermore, AI has shown exceptional support for diabetic self-management. It provides patients with the personalized information they need to live healthier lifestyles and manage their diabetes more effectively. As a result, AI is being used to aid self-management and as a strategic tool for providing treatment to those who live in remote locations with few readily available medical specialists for routine visits.

AI is effective in monitoring diabetic retinopathy consequences in addition to improving diabetes care by developing algorithms that can correctly predict the onset and incidence of diabetic retinopathy, among other issues.

To analyze social media activity, physical and mental health, and lifestyles of individuals within a geographic area or demographic population, machine learning is predominantly used in AI. This can be beneficial for regions that experience logistical difficulties, a shortage of eye specialists, or excessive healthcare facility visit costs.

Investment in AI is required both in India and elsewhere in the world to close the management gap in eye care, particularly in ways that can make managing diabetic retinopathy cost-effective, simpler, and more practical, and ultimately reduce vision loss and blindness in the nation.

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