Perspective Chapter: Artificial Intelligence in Multiple Sclerosis

In recent times, the words artificial intelligence, machine learning, and deep learning have been making a lot of buzz in different domains and especially in the healthcare sector. In disease areas like multiple sclerosis (MS), these intelligent systems have great potential in aiding the detection and prediction of disease progression and disability, identification of disease subtypes, monitoring, treatment, and novel drug-target identification. The different imaging techniques used to date in multiple sclerosis, various algorithms such as convolutional neural network, Support Vector Machine, long short-term memory networks, JAYA, Random Forest, Naive Bayesian, Sustain, DeepDTnet, and DTINet used in the various domains of multiple sclerosis are explored, along with used cases. Hence it is important for healthcare professionals to have knowledge on artificial intelligence for achieving better healthcare outcomes