همایش بین المللی هوش مصنوعی

صفحه اصلی / اولین همایش بین المللی هوش مصنوعی

A Comprehensive Review of Machine Learning Applications in Multiple Sclerosis: From Diagnosis to Prognosis and Treatment Response Prediction

نویسندگان :

Mahdie Azizi hashjin¹ Babak Nouri-Moghaddam² Abbas Mirzaei³

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 :

Deep Learning،Classification،Multiple Sclerosis،MRI

چکیده :

Multiple sclerosis (MS) is a chronic, debilitating disease of the central nervous system that poses significant challenges in diagnosis, prognosis, and treatment. Machine learning (ML), a subfield of artificial intelligence, has emerged as a promising tool to address these challenges. This review explores the growing applications of ML in MS research, focusing on diagnosis, prognosis, and treatment response prediction. ML algorithms, including support vector machines, decision trees, and neural networks, have demonstrated high accuracy in distinguishing MS patients from healthy individuals or those with other neurological conditions using data sources such as magnetic resonance imaging (MRI) scans, genetic data, and clinical records. ML models are also being developed to predict disease progression and treatment responses, paving the way for personalized medicine. Despite the promising potential of ML in advancing MS care, challenges remain in data quality, model interpretability, and clinical implementation. Future research should address these issues to develop robust, clinically applicable ML tools for personalized MS management.