Unraveling Autoimmunity: Exploring Etiological Factors and Machine-Learning Applications in Varied Autoimmune Disease

The human body’s immune system has a crucial and essential role in protecting humans from foreign substances that might hinder bodily functions, including fungi, viruses, and other pathogens. But sometimes, our immune system is unable to distinguish between foreign cells and our own cells which turns into a complex disease known as autoimmune disease. The reason for not recognizing its cells is not known, which creates a lot of queries that need to be addressed. Since the actual cause of the disease is not known, potential causes can be identified with the help of ongoing research and machine learning. There are hundreds of diseases in the autoimmune category, and machine learning and deep learning models are applied to a variety of problems, including the co-existence of diseases, detection, classification, glucose monitoring, medication effects, managing big datasets, and analyses. This paper examines the research articles from 2007 to 2023 to extract information about the effects and possible trigger factors of rheumatoid arthritis, pemphigus, and type 1 diabetes. It also illustrates the challenges and constraints associated with each machine-learning technique that is utilized in a variety of ADs, in addition to its own efficacy.