How is AI impacting eye care?

Artificial intelligence (AI) technologies are already transforming the healthcare sector. This includes helping eye care professionals deliver more for their patients.

AI technologies are defined as systems that can take in data from their environment and use it to replicate human tasks. This includes making decisions, understanding and interpreting language or imagery and solving problems.

Just like a human, AI-enabled hardware and software can also change their outputs or actions based on previous results. This means work can be completed without assistance or intervention.

Smart robotics, machine learning and deep learning are all specific types of AI. With their particular and powerful capabilities, they have already been transforming various sectors, including healthcare.

Indeed, it's estimated that AI technologies in the healthcare market will be worth more than $200 billion by 2030 thanks to the benefits they can bring to patients and professionals. This growth is replicated in eye care, which is already enjoying the advantages AI can bring.

This article will explain the benefits of AI for people living with eye conditions and the eye care professionals that treat them, both now and in the future.

How is AI being used in eye care?

The full potential for using AI in eye care is yet to be realised, with many studies ongoing. However, a few AI tools are already being used by optometrists and other eye care professionals as part of their practice.

These include:

  • Scan analysis: once they’re fed with thousands of Optical Coherence Tomography (OCT) scans or retinal images, AI systems can start to learn and identify inconsistencies, damage or potential problems.
  • Referral decision-making: based on large data sets, machine or deep learning systems can weigh up the evidence and decide whether to make a referral to the hospital or for further treatment.
  • Diagnosis tools: though some asymptomatic signs may be difficult for human professionals to pick up, these can be learned and identified by AI systems, enabling faster and more objective diagnosis.

    Some professionals may be worried that the introduction of AI technologies into eye care may impact their own job roles. However, studies have shown that the benefits of these tools mean more optometrists and ophthalmologists are now receptive to the use of AI in treating conditions like glaucoma and age-related macular degeneration (AMD).

    One survey found that, though 53% of professionals were concerned about the accuracy of AI-powered diagnoses, 72% believed it would improve optometry practice. As such, AI technologies are expected to become an increasingly common part of detecting, diagnosing and treating eye conditions.

    How is AI helping eye care professionals?

    So what exactly are the advantages this technology can bring and how is it helping optometrists deliver better eye care?

    Greater confidence with OCT

    Analysing OCT scans is a key part of the diagnosis process for retinal conditions. Yet comprehensive training is often expensive and difficult to access, with 36% of professionals learning the skills via a webinar or conference.

    With experience also being a key factor in the accuracy of OCT interpretation, some optometrists may lack confidence in this skill.

    AI-enabled tools can be fed with thousands of OCT scans and programmed via an algorithm to understand and recognise potential signs of eye conditions in the images. Plus, if they’re equipped with machine learning capabilities, they can learn from historical decisions and improve the accuracy of their diagnoses.

    This gives eye care professionals a powerful and objective way to interpret OCT scans, taking pressure off their own skills and experience.

    Increased diagnosis accuracy

    The objective analysis of eye scans and images possible with AI-enabled software significantly improves the accuracy of diagnoses. AI has already been used to make referral or diagnosis judgements based on retinal images and OCT scans.

    Alongside a data-based, evidence-backed diagnosis, ophthalmologists and optometrists will also be sent the system’s full judgement and conclusions. Gaining access to this level of detail means professionals can communicate this to patients and recommend more effective treatments.

    Some eye care professionals worry about the accuracy of these tools. However, a survey found that 30.5% of optometrists admit they have no idea if they miss any minor, early or rare pathology at all.

    As Chief Executive Officer and Scientist of the charity Action Against Age-related Macular Degeneration (AAAMD) Dr Wen Hwa Lee explains, the data-based nature of these technologies makes their judgements highly accurate in comparison to humans.

    He said, “AI-derived algorithms trained on large sets of ophthalmic images (such as OCT scans) can mathematically narrow down on subtle nuances, patterns and features and use those to identify certain diseases.”

    Saving professionals’ time

    Alongside greater objectivity and accuracy, AI technologies can help to speed up repetitive processes. By taking these tasks off the desks of ophthalmologists and optometrists, these technologies can also free up professionals’ schedules.

    Instead, eye care professionals can use this time to do more complex tasks. It also increases their availability for patient-facing work such as assessments, explaining their treatments and answering their queries.

    With faster diagnoses, eye care professionals can also help more patients get the treatment they need earlier. This means patients can take the steps they need to transform their lifestyle, something that’s essential for slowing the progression of conditions such as AMD or glaucoma.

    Providing an expert partner

    Whether it's assessing scans, reviewing patients or recommending treatments, eye care professionals often look to consult with their colleagues when dealing with complex issues or controversial scans. However, due to demands on professionals’ time, this isn’t always possible.

    By having appropriate AI-enabled tools within a practice, ophthalmologists and optometrists can use them to get an objective, accurate and detailed judgement. This will help them solve more difficult diagnoses and recommend the right treatments based on data, without having to rely on colleagues’ expertise.

    In short, AI will help eye care professionals deliver better eye care faster.

    How will AI impact the future of eye care?

    Due to the ageing global population, the prevalence of eye conditions is set to increase in the near future.

    For example, the Royal National Institute of Blind People (RNIB) estimates that there will be an 18% increase in people living with glaucoma by 2032. Similarly, the 700,000 people currently experiencing sight loss as a result of AMD are set to increase by 25% up to 2032.

    As more people start to experience symptoms of vision loss and look for diagnosis and treatment, AI technologies will be essential to helping eye care professionals cope with this greater demand. As such, projects such as the retinal images database being built and analysed by AAAMD are essential to scaling up the use of AI-enabled tools.

    As Chief Executive Dr Wen Hwa Lee explained: “With so much pressure on the NHS… it is now not only logical but necessary to better call upon primary care.”

    “If optometrists can be equipped with tools to help them send only the people who absolutely need to go to hospital, we already increase the productivity of the NHS without a single pound being injected into the system.”

    By increasing productivity and accuracy, AI technologies won’t just help eye care professionals complete their work more efficiently, but provide better care to their patients too.

    At Ocuplan, we’re also working hard to make this possible. That’s why we’ve created our new, free service. By providing lifestyle advice, expert help and appointment reminders, this service helps ophthalmologists and optometrists support their patients and deliver better care.

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    About OcuPlan

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