Diabetic retinopathy is a serious and potentially blinding complication of diabetes. Despite significant advances in the treatment of the disease, it remains the leading cause of vision loss in adults worldwide. What makes diabetic retinopathy particularly dangerous is that it is often asymptomatic in its early stages, meaning patients may not even know they have the disease until it is significantly advanced. At this stage, the eye damage may be irreversible, so early detection and treatment are crucial.
Screening for diabetic retinopathy can be a difficult task for ophthalmologists and healthcare providers. The large number of patients requiring screening combined with the complexity of diagnostic tests makes this a daunting task even for experienced professionals. Due to limited resources and a shortage of ophthalmologists in many areas, it can be difficult to offer timely screening to all at-risk patients. Additionally, the process can be time-consuming and burdensome for patients, many of whom may not have access to transportation or other means to travel to a clinic for screening. These challenges can lead to delays in diagnosis and treatment, leading to unnecessary vision loss and other complications.
How Have They Changed Ophthalmology With Artificial Intelligence?Google compiled a dataset containing more than a million retinal scans of diabetic patients and enlisted the help of 50 ophthalmologists to manually review each image and assess its level of diabetic retinopathy. This process provided a huge amount of labelled data that was used to train a deep learning algorithm. The algorithm is designed to identify certain patterns and features in studies that suggest diabetic retinopathy and predict the likelihood of the disease appearing on a new scan. With this algorithm, it is now possible to automate screening, allowing for more efficient and accurate detection of diabetic retinopathy.
ApplicabilityWhen the algorithm is enabled, uploading a retinal scan for analysis is sufficient to determine if signs of diabetic retinopathy are present and what grade to assign instead.
By automating the screening process and enabling faster and more accurate detection of diabetic retinopathy, Google’s algorithm can significantly increase the number of patients who can be screened and prioritise treatment for patients with more severe cases, ultimately improving outcomes and saving more lives. people from the dark.