Over the last several decades, technology has infused nearly every sector of business throughout the world. While most connect the impact of technological advances with broad consumerism and business efficiencies, recent developments are starting to change the way healthcare is delivered in developed countries. There are now several ways in which medical care is given and received, but the most notable advances have come by way of artificial intelligence. Leading technology companies including Google have even created subsidiaries to focus in on healthcare improvements with the help of AI, based on its far-reaching implications for patient care in countless aspects of diagnosis and treatment.
Artificial intelligence in healthcare has come under the spotlight for diabetic patients in the last few months thanks to Google’s DeepMind offshoot. Through its targeted research, DeepMind has developed a diagnostic tool to assist with the often complex issue of diabetic retinopathy. A significant number of adults with diabetes have the potential to develop the debilitating eye condition as a side effect of the disease, and without proper intervention early on, retinopathy can lead to complete blindness in some patients. The DeepMind project has shown great promise in assisting in the diagnosis of diabetic retinopathy, aimed at giving patients a more accurate diagnosis earlier in the onset of the condition. In the US, the FDA has recently approved a similar diagnostic screening for diabetic retinopathy that paves the way for continued success with artificial intelligence in healthcare.
Why Diabetic Retinopathy
Adults living with diabetes have the potential to develop retinopathy over time, particularly when management of the condition is not maintained over one’s lifetime. Diabetic retinopathy develops when the blood vessels found in the retina are damaged, leading to visual distortions like blurriness, color blindness, or dark areas. In the worst cases, when diabetic retinopathy is not diagnosed quickly, patients may experience full loss of eyesight that cannot be reversed. Adults with Type 1 or Type 2 diabetes may develop retinopathy as their condition progresses, or when blood sugar levels are not monitored and controlled over time.
Diabetic retinopathy has been the focus of technology firms in the healthcare sector not only because of its devastating outcomes, but also given the need for faster, more accurate diagnosis in practice. Some patients do not experience any symptoms at the onset of retinopathy, while others have immediate issues like blind spots or haziness. When symptoms appear, a full review of the patient’s issues is often the next step. However, when symptoms are not apparent, there may be no catalyst for a diagnostic screening for the condition specifically. To avoid serious complications with diabetic retinopathy in the future, a new way of detecting the condition is necessary.
AI Diagnostic Advancements
Receiving a screening for eye disease as a diabetic patient is a crucial part of a comprehensive care plan. However, not all providers are prompted to offer up such a screening unless symptoms are severe. A UK specialist in medical negligence claims explains that when diabetic retinopathy screening is not part of the normal diabetic care pathway, a proper diagnosis may go overlooked for an extended period. This leads to adverse outcomes for patients that cannot be remedied with medication or surgical intervention. Part of the reason behind a smaller number of retinopathy screenings is the time crunch faced by many providers, combined with a lack of expertise in the area. Artificial intelligence in the realm of diagnostic screenings helps eliminate these issues on a grand scale.
Google’s DeepMind project in the realm of diabetic offers a viable solution for missed or delayed diagnosis thanks to its AI component. In trial results of the screening exam, the device was able to show earlier signs of eye disease with a high level of accuracy, without the assistance of a medical professional. This is possible because the device utilises thousands of medical images and retinal scans of past patients to determine what signs may lead to a retinopathy diagnosis. The algorithms built into the device then compare the data with a patient’s eye screening to come up with a diagnosis or an all clear. While the technology for diabetic retinopathy screening must still successfully complete clinical trials before it is released for use to the public, the advancements in this arena offer a great deal of hope for diabetic patients and their families.
