The development of a state-of-the-art integration system for the analysis and classification of magnetic resonance imaging in order to make an early diagnosis of Alzheimer’s has its origin in the University of Kaunas, located in Lithuania.The project is based on the analysis of a functional magnetic resonance imaging (fMRI) can identify the regions of the brain associated with Alzheimer’s, especially when the symptoms are not clear, but to date performing this type of process requires a lot of time and specific knowledge on the part of doctors. It is at this point that cutting-edge technologies such as Deep Learning and Artificial Intelligence come in. In this regard, the researcher Rytis Maskeliunas pointed out that “Technologies can encourage the search for help and timely diagnosis (…) We were able to delegate image processing (resonances) to machines that can complete it more quickly and accurately.” This integrated system makes it possible to classify MRIs by detecting those with signs of cognitive impairment, thanks to an algorithm that in turn could be developed into software in charge of analyzing the collected data and notifying medical personnel in case of any anomaly. In this line Maskeliunas pointed out that “New advances will make medicine more accessible and cheaper. While they will never really replace the medical professional, technologies can encourage the search for timely help and diagnosis.” It should be noted that Alzheimer’s is currently the most common form of dementia, covering almost 70% of cases according to the World Health Organization (WHO), and to date no cure has been found for this disease, but if there are treatments that can help control or delay symptoms for a while, that is why early detection is essential to face the disease.