Abdul Majeed Kaamran¹*, Christopher Röhrig², Vincezo Costiolga³ and Afü Röhrig⁴

¹C.E.O , AAH Natürlich - GmbH, Germany
²Technical Advisor, AAH Natürlich - GmbH, Germany
³President, European Medical Association , Brussels, Belgium
⁴Scientific Director, Epigenetics , European Medical Association , Brussels, Belgium

*Corresponding Author: Abdul Majeed Kaamran, C.E.O , AAH Natürlich-GmbH, Germany.

Received: August 22, 2025; Published:August 30, 2025

Abstract

GI intolerance is not a single disease but rather a clinical endpoint for numerous distinct mechanisms, including enzyme deficiencies, dysregulated gut motility, profound imbalances in the gut microbiome, aberrant immune system activation, and disruptions along the gut-brain axis. Consequently, a "one-size-fits-all" approach to diagnosis and treatment is rendered largely ineffective into this complex clinical landscape emerges Artificial Intelligence (AI) as a transformative technological paradigm. AI, and its subfields of machine learning (ML) and deep learning (DL), offers a powerful new framework for addressing the inherent complexity of GI intolerance. Far beyond simple automation, AI provides the capacity to integrate and analyse vast, heterogeneous datasets that were previously intractable. To appreciate the transformative potential of AI, it is first necessary to delineate the intricate clinical "problem space" that it seeks to address. The current understanding of adverse food reactions is a mosaic of distinct pathophysiological processes that converge on a remarkably similar set of clinical manifestations. With the help of blood protein test and blood physics we can ascertain the right quantity and quality of the diet.
Gastrointestinal (GI) intolerance represents a pervasive and clinically challenging entity, affecting more than 20% of individuals in industrialized nations. It manifests as a constellation of non-specific yet burdensome symptoms, including abdominal pain, bloating, nausea, and altered bowel habits, which significantly impair quality of life. The diagnostic landscape is clouded by a profound symptomatic overlap between a wide spectrum of underlying conditions. monitoring it with AI assisted tools for a better quality of life

Keywords: Gastrointestinal; Food Allergy; Intolerances; Nutrition Plan; AI; Artificial Intelligence; Diet

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Citation

Citation: Abdul Majeed Kaamran., et al. “Navigating Gastrointestinal Food Allergy and Intolerances Further Supporting the Correctives for the Intolerances with an AI based Diet and Nutrition Plan A Systemic Review - Meta Data Analysis".Acta Scientific Gastrointestinal Disorders 8.9 (2025): 32-39.

Copyright

Copyright: © 2025 Abdul Majeed Kaamran., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.