AI-Guided Histopathological and Molecular Phenotyping of Salivary Glands in Sjögren’s Disease: Subtyping, Mechanistic Insights, and Translational Implications—A Systematic Review and Structured Functional Synthesis

Background/Objectives: Salivary-gland biopsy is central to Sjögren’s disease (SjD) assessment, but conventional measures incompletely capture glandular heterogeneity. This systematic review evaluated artificial intelligence (AI)/machine learning (ML) applications to SjD salivary-gland histopathology and molecular profiling, including biological and translational validation.

Methods

PubMed, Scopus, and Embase were searched. Eligible studies used salivary-gland tissue as the primary analytical substrate or provided substantive glandular validation of systemic AI/ML findings. Evidence was synthesized functionally because of methodological heterogeneity.