  Tumors can manifest in various forms and in different areas of the human
body. Brain tumors are specifically hard to diagnose and treat because of the
complexity of the organ in which they develop. Detecting them in time can lower
the chances of death and facilitate the therapy process for patients. The use
of Artificial Intelligence (AI) and, more specifically, deep learning, has the
potential to significantly reduce costs in terms of time and resources for the
discovery and identification of tumors from images obtained through imaging
techniques. This research work aims to assess the performance of a multimodal
model for the classification of Magnetic Resonance Imaging (MRI) scans
processed as grayscale images. The results are promising, and in line with
similar works, as the model reaches an accuracy of around 98\%. We also
highlight the need for explainability and transparency to ensure human control
and safety.
