REVUE ALGERIENNE D’ALLERGOLOGIE
Volume 10, Numéro 2, Pages 10-16
2026-01-05
Immune-mediated Multi-organ Syndromes: Diagnostic Challenges And The Role Of Artificial Intelligence In Internal Medicine
Authors : Dr Larbani Salim . Pr Lyazidi Nabila . Pr Ayoub Soraya .
Abstract
Immune-mediated multi-organ syndromes pose significant diagnostic difficulties in internal medicine, especially when clinical presentations are atypical or overlap multiple disease entities. Syndromes such as mixed connective tissue disease (MCTD) and anti-synthetase syndrome (ASS) embody this complexity, often blending signs of systemic lupus erythematosus, systemic sclerosis, myositis, and other connective tissue diseases. The boundaries between these syndromes remain poorly defined, leading to diagnostic delays and therapeutic uncertainty. Amid this diagnostic chaos, artificial intelligence (AI) offers a compelling solution. By leveraging machine learning techniques, AI can synthesize vast clinical and biological datasets to generate predictive models and aid diagnostic reasoning. This review examines the clinical and immunological characteristics of key overlap syndromes, dissects the limitations of current diagnostic frameworks, and explores how AI can support internists in managing these challenging cases. A conceptual diagnostic decision tree incorporating AI-supported logic is presented to illustrate how such systems could enhance diagnostic accuracy, reduce time to diagnosis, and promote earlier therapeutic interventions.
Keywords
Autoimmune diseases, overlap syndromes, artificial intelligence, internal medicine, diagnosis, connective tissue disorders, anti-synthetase syndrome, systemic autoimmunity
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