Eye health services have more patients than specialist doctors can handle. For example, eye scans are done more often than doctors can check them. This causes delays in finding and treating eye problems. Delays can lead to permanent loss of sight in diseases like diabetic retinopathy or age-related macular degeneration.
An AI system made by University College London (UCL), DeepMind Health, and Moorfields Eye Hospital has learned from thousands of eye scans without patient information. It can suggest referrals for over 50 eye diseases. This AI is as accurate as expert doctors and makes correct referral calls over 94% of the time. It looks at optical coherence tomography (OCT) scans, a common way to image eyes, to find signs of serious eye conditions that need quick care.
This AI works with many types of eye scanners, not just the ones it trained on. This helps hospitals in the U.S. use it with different equipment brands. It makes it easier to add the technology in many places.
Dr. Pearse Keane, an eye doctor at Moorfields Eye Hospital, says early diagnosis is very important to stop sight loss. He explains that delays happen because tests take longer for doctors to review. This AI helps by spotting patients who need urgent care first. It may improve patient results and lessen the load on specialists.
AI can help find and treat eye diseases early. This is good for patients and hospitals. Patients can keep better vision and have a higher quality of life. Hospitals can use resources smarter by treating the most urgent cases faster.
In the U.S., where healthcare is often busy, AI can make eye care faster and better. As approvals and studies continue, AI might become a key tool in eye care departments at many hospitals and health groups.
The U.S. Department of Health and Human Services supports AI to help with problems caused by too much clinical work. AI that works as well as human experts could help meet this high demand.
AI can do more than just help with diagnosis. Hospital administrators and IT workers should think about how AI-driven automation can lower the work load and improve communication with patients.
In eye care, AI automation can help in many ways:
Using AI in eye care needs careful planning and money. Hospital leaders must check rules about data privacy and if the AI works with their clinical systems. The AI system by UCL and DeepMind is still in testing and waiting for approval before wide use.
Pilot programs help hospitals try AI first to see how it affects work and patient care. Working with AI providers who know medical workflows, such as Simbo AI for phone automation, is also important.
AI tools keep improving since they are built on research and data from many patients. This helps the AI work well in real hospitals and makes doctors trust its advice.
If AI can spot eye diseases early and guide good referrals, fewer people may lose vision in the U.S. Early diagnosis often means conditions can be managed better before damage becomes permanent.
Since more people need eye care, AI can help by easing doctor shortages while keeping care quality high. Hospitals using AI may see better patient flow, smarter use of staff, and overall better care.
As AI spreads to other medical areas, lessons from eye care can help hospitals use the technology in other fields. Adding AI and automation to daily work is becoming needed as patient numbers grow and care gets more complex.
Hospitals in the U.K. show how research and clinical work can join with technology. U.S. hospitals can learn from this and improve eye care by using AI to reduce delays and help patients get the treatments they need on time.
Hospitals can use AI for more than diagnosis. It can also help make office and clinical work smoother and improve patient care.
Hospitals in the U.S. that want to stay current and meet patient needs should think about adding AI diagnostic tools and automated workflows to eye care. The technology is accurate and adaptable, helping improve eye care quality.
By using AI systems from the U.K. and new automation tools, U.S. healthcare providers can make eye care better. They can improve patient results, use resources well, and give patients better experiences. As AI grows and gets approved, eye care in U.S. hospitals is likely to change for the better.
AI has been developed to recommend correct referral decisions for over 50 eye diseases, demonstrating accuracy comparable to expert clinicians in identifying features of eye disease and suggesting appropriate patient care.
The AI system prioritizes patients needing urgent attention by analyzing OCT scans and identifying serious eye conditions, helping to avoid delays in diagnosis and treatment.
The AI system provides explanatory visuals of detected disease features and expresses confidence levels in recommendations, facilitating clinician scrutiny and decision-making.
It can be easily applied to various eye scanners, not limited to the particular model used for training, ensuring broad usability and adaptability as technology evolves.
The AI was able to make correct referral recommendations over 94% of the time, matching the performance capabilities of expert clinicians.
Early diagnosis is crucial for effective treatment of eye conditions, potentially preserving sight and improving long-term patient outcomes.
The next step involves clinical trials to evaluate the technology’s safety and effectiveness before it can be approved for use in clinical settings.
The project enhances a valuable dataset for ongoing medical research and may provide free access to the technology across 30 UK hospitals for five years if clinical trials succeed.
The project involved collaboration between UCL, DeepMind Health, and Moorfields Eye Hospital, uniting top healthcare and technology professionals.
The research exemplifies how AI can significantly enhance healthcare delivery, particularly in preventing avoidable sight loss globally, signifying a transformative step in medical care.
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