همایش بین المللی هوش مصنوعی

صفحه اصلی / اولین همایش بین المللی هوش مصنوعی

Attention Mechanisms in Deep Learning for Multiple Sclerosis Classification

نویسندگان :

Mahdie Azizi hashjin¹ Mahsa Yaghoobi² Babak Nouri-Moghaddam³

1- Department of Computer Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran 2- Department of Computer Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran 3- Department of Computer Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran

کلمات کلیدی :

Multiple sclerosis،attention mechanisms،deep learning،medical imaging،MRI،classification models،diagnostic tools،feature extraction

چکیده :

This research paper reviews the application of attention mechanisms in deep learning models to enhance the classification of multiple sclerosis (MS) from medical images, particularly MRI scans. The authors examine various attention mechanisms—such as spatial, channel-wise, and self-attention—and assess their impact on diagnostic accuracy and efficiency. Several studies utilizing different AI techniques for MS diagnosis are reviewed and compared, emphasizing the strengths and challenges of integrating attention mechanisms. The paper concludes by discussing the potential benefits and limitations of these methods in clinical practice, while suggesting future research directions to improve data quality, computational efficiency, and model generalizability. The ultimate objective is to develop more accurate and reliable diagnostic tools for MS.