Imagine walking into a doctor's surgery and, instead of a specialist taking a long time to analyze an image of the back of your eye, a computer, in seconds, provides a precise diagnosis, assesses the risk of disease progression and suggests a possible treatment plan to your eye doctor. This is not a distant vision of the future, it's a reality that's rapidly taking shape, thanks to Artificial Intelligence (AI). In recent years, the application of AI in medicine has grown exponentially. And few areas have benefited as much as Ophthalmology. From screening to monitoring diseases such as diabetic retinopathy, age-related macular degeneration (AMD), glaucoma and retinopathy of prematurity, technology is gaining a prominent role in supporting diagnosis and personalizing eye care. But how does this technology work? And what changes can it bring to the way we look after our sight?

What is Artificial Intelligence?

Artificial Intelligence is a branch of computer science that seeks to imitate the human ability to reason, learn from experience and make decisions. Instead of being programmed with rigid instructions, AI systems 'learn' from large volumes of data such as millions of medical images to recognize patterns and predict outcomes. In practice, this means that a computer can learn to distinguish a healthy eye from one with early signs of disease, with an accuracy often comparable to that of an experienced doctor. This learning is possible through methods such as deep learning, where artificial neural networks inspired by the human brain are trained to detect subtle changes in images.

Shortage of specialists

One of the major challenges facing global eye health is the shortage of ophthalmologists, especially in remote areas or those with limited resources. In many countries, the number of professionals is not sufficient to meet the needs of the population, which leads to delays in the diagnosis and treatment of diseases that can cause blindness.

AI can help bridge this gap. For example, devices equipped with intelligent algorithms can analyze photographs of the retina and indicate whether there are signs of diseases such as diabetic retinopathy, one of the main causes of blindness in adults. This automatic screening allows only suspicious cases to be referred for medical evaluation, saving time and resources.

Diabetic retinopathy

The latest studies are encouraging. A system approved in the US by the FDA, for example, can detect diabetic retinopathy with more than 90% sensitivity and specificity - values comparable to those of human experts. Diabetes is a silent epidemic that affects more than 400 million people worldwide. One of its most serious complications is diabetic retinopathy, which can lead to blindness if not detected early. The good news is that this disease can be identified through a simple photograph of the back of the eye. And this is where LA comes into play: systems such as EyeArt or Retmarker (the latter developed in Portugal, more specifically in Coimbra) analyze these images in seconds, with high reliability, and classify the patient's risk. Some of these systems are already being used in large-scale screening programs, including in Portugal.

Limits and challenges

Despite the advances, it is important to recognize that AI is not perfect and should not replace the doctor. Algorithms work well when trained with large volumes of good quality data, but can fail in rare or atypical situations. There are also legitimate concerns about the privacy of patient data, the risk of algorithmic bias and the lack of transparency in certain models (the so-called black box).

Conclusion

AI is transforming the way we see. By enabling earlier, faster and more accessible diagnoses, it is paving the way for fairer, more efficient and more personalized ophthalmology. There are still challenges, but the horizon is promising. After all, if the eyes are the mirror of the soul, perhaps AI is the mirror of a more humane, precise and inclusive medicine.

In Portugal

Systems that identify diabetic retinopathy are already in use in our country. A leap forward in technology that makes it possible to combat an epidemic that affects more than 400 million people worldwide.