The DORIA system (Diagnostic Ophthalmology Robotised by Artificial Intelligence) has revolutionized ophthalmic care in several specialty centers in Madrid linked to the La Paz University Hospital. This innovative system allows more than 100 tests to be carried out in just eight minutes, providing all the data needed to diagnose dozens of eye pathologies. Thanks to its implementation in the José Marvá, Peñagrande and Colmenar Sur centers, the waiting time for a diagnosis in this specialty has been significantly reduced, improving patient care and optimizing hospital resources.
Félix Armadá-Maresca, head of the Ophthalmology Department at La Paz University Hospital, told Alimente that this system makes the hospital the first tertiary center in Europe to adopt this technology. Furthermore, although for the time being it is the only hospital in Spain to use it autonomously, Armadá-Maresca confirmed that other centers are already working on its implementation. The specialist explained that DORIA works by carrying out a series of tests which, using artificial intelligence, offer a probabilistic diagnosis of various pathologies, such as glaucoma, keratoconus, cataracts, among others. Depending on the results, the system indicates whether the risk of suffering from one of these diseases is low, medium or high and allows patients to be quickly referred to the corresponding specialized service.
The system, which has already been used to screen more than 2,000 people, has reduced the number of patients incorrectly referred for specialist consultations by 44%, resulting in a considerable reduction in waiting lists. Armadá-Maresca explained that the system carries out a very efficient initial screening of patients referred by family doctors, preventing those who don't need specialized care from overcrowding ophthalmology appointments. In this way, ophthalmologists can concentrate on seeing patients who really need specialized treatment, such as those with glaucoma, cataracts or retinal pathologies.
Among the diseases that DORIA can rule out in just a few minutes are cataracts, narrow-angle glaucoma, keratoconus, corneal leukomas, intraocular lens opacification and age-related macular degeneration, as well as early detection of diabetes complications, among others. The system also generates a detailed report that includes the risk or probability of having an eye pathology, facilitating earlier and more accurate treatment.
The incorporation of DORIA not only aims to simplify ophthalmic diagnosis, but also to democratize access to advanced tests for all patients, regardless of their location. By automating the screening of eye pathologies, this technology allows patients to access specialized eye care more quickly, significantly reducing waiting lists. Armadá-Maresca explained that without this tool, appointments for new patients would be scheduled for a year from now, but thanks to DORIA they have been reduced to a much shorter timeframe.
AI in medicine
The application of artificial intelligence in medicine is not new, but its impact is radically transforming the way diseases are diagnosed. In addition to DORIA, systems such as Da Vinci, the robot surgeon, have enabled significant advances in other fields of medicine. Just a few months ago, Da Vinci performed a partial liver removal on a living donor in Spain, while artificial intelligence allowed a doctor in Spain to operate on a patient in Beijing, in what was the first transcontinental robotic nephrectomy performed from Europe.
Armadá-Maresca stressed that artificial intelligence based on image analysis has enormous potential to continue transforming medicine, especially in specialties such as radiology, dermatology and pathological anatomy, where image analysis is fundamental for diagnosis. According to the expert, the use of these systems can significantly improve the early diagnosis of diseases, with a hit rate that in some cases will surpass that of human specialists.
In short, the introduction of DORIA in Madrid's specialty centers is improving the quality and speed of ophthalmic diagnoses, easing the workload of health professionals and reducing waiting lists, democratizing access to more efficient specialist care.