Classification of Multiple Sclerosis (MS) and Healthy-Control blood samples using Transfer Learning

Multiple sclerosis (MS) is a severe inflammatory condition of the central nervous system
(CNS) affecting about 2.5 million people globally. It is more common in females, usually
diagnosed in their 30s and 40s, and can shorten life expectancy by 5 to 10 years. While
MS is rarely fatal; its effects on a person's life can be profound, which signifies
comprehensive management and support. Most studies regarding MS focus on how
lymphocytes and other immune cells are involved in the disease. However, little attention
has been given to red blood cells (erythrocytes), which might also be important in
developing MS. Artificial intelligence (AI) has shown significant potential in medical
imaging for analyzing blood cells, enabling accurate and efficient diagnosis of various
conditions through automated image analysis. The project aims to implement an AI
pipeline based on Deep Learning (DL) algorithms (e.g., Transfer Learning approach) to
classify MS and Healthy Blood cells.