**1. Introduction**

Autoimmune diseases can be defined as the inability of the human system to distinguish its own bodies from foreign bodies [1, 2]. The diagnosis of autoimmune diseases is not easy. However, with the emergence of the serological tool and our progress in understanding the science of the immunology, antibodies provide an excellent role in the prediction of GI autoimmune diseases. They serve as markers for the prediction or confirming the presence of an autoimmune disease. The emergence of artificial intelligence (AI) and the integration of machine learning (ML) algorithms in many applications and their incorporation into the health sector as well open the gate for improved diagnosis and management of the diseases. In ADs, they could be great asset as many of the diagnostic tests depend on imaging techniques that their interpretations could vary from one clinician to another. The treatment of GI autoimmune

diseases could be variable from the need for elimination diets to surgical interventions depending on the case and the disease.

In the previous chapter, we provided an introductory background on autoimmune diseases, definition of pathophysiology and etiology of autoimmune diseases, a review of the five most common GI autoimmune diseases, the role of psychological association with GI Tract autoimmunity, and microbiome and AD: The Gut–Brain Axis. In this chapter, which is a continuation of the second chapter we discuss other aspects that include shading the light and in-depth review of the fascinating roles of antibodies as predictors for the GI autoimmune diseases, the role of dietary and nutritional implications, the use of artificial intelligence in diagnosis of GI autoimmune diseases, and the treatment of GI autoimmune diseases.
