Karim . Gasmi

In these last years, Convolutional Neural Network (CNN) models have shown significant performance
improvements in several fields as image classification, and Natural Language Processing (NLP). Given
their success in image classification, it seems that they should have an important impact on image
retrieval.
However, until now, such success has not yet been accomplished for medical image retrieval, especially
text-based medical image retrieval (TBMIR) tasks. It could be due to the complexity of the ranking

Alzheimer's disease presents a significant and unyielding challenge, particularly among the elderly
population, where its insidious progression of memory loss casts a profound global impact, especially on
individuals aged 65 and above. Detecting this condition early is paramount for a comprehensive
evaluation of its evolving symptoms. However, the current reliance on manual diagnosis by healthcare
professionals proves to be both labor-intensive and susceptible to inaccuracies, primarily due to the sheer

In recent years, augmented reality has emerged as an emerging technology with huge potential in imageguided surgery, and in particular, its application in brain tumor surgery seems promising. Augmented
reality can be divided into two parts: hardware and software. Further, artificial intelligence and deep
learning in particular have attracted great interest in research to be used in the medical field, especially in
the diagnosis of brain tumors. Recent research from the Saudi Cancer Registry, conducted in 2014, found