AI-Powered Diagnosis of Biermer's Disease: Handling Uncertainty in Clinical Decision-Making

Abstract

Biermer's disease is a chronic autoimmune disease that affects the upper part of stomach, the fundus. This disease causes biomarkers against the parietal cells and the intrinseque factors, leading to a malabsorbtion of vitamin B 12 and iron in the stomach. However, these markers aren't specific to Biermer's disease, which creates uncertainties during the diagnostic process, making this disorder misdiagnosed and the clinical interpretation challenging. Conventional techniques are not able to differentiate Biermer from other illnesses. This inability delays, significantly, diagnosis, causing irreversible neurological complications. To overcome the inherent uncertainties of the diagnostic, we propose a fuzzy decision Support System for Biermer's Diagnosis. Our approach uses expert medical knowledge to evaluate important parameters and build the fuzzy rule basis. The system that has been developed is a significant step forward in the accurate diagnosis of Biermer's disease and addresses the obstacles to an earlier intervention, thereby preventing severe neurological complications.

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