Integrating Artificial Intelligence with Biological and Multimodal Data for Predicting, Diagnosing, and Managing Inflammatory Diseases: A Comprehensive Review

Inflammatory diseases include a varied array of morbidity and mortality as well as a variety of forms (acute or chronic) of disease.As a result, they represent a significant therapeutic challenge driven by dysregulated immune responses, presenting substantial dynamic immune response, molecular variability and variability in the course of disease.The development of sufficient theranostic options for inflammatory diseases by conventional methods has been shown to be inadequate based on their complexity of pathogenesis.Artificial Intelligence (AI), as a powerful platform in integrating multidimensional biological, clinical and imaging data is increasingly addressing these challenges.This review aims to provide a summary of how AI is being utilized across the three main areas of inflammatory disease research including understanding the mechanisms of inflammatory diseases, onset and course of inflammatory diseases predicting and strategies for inflammatory diseases diagnosing and managing.Machine learning, deep learning and the utilization of multimodal data are all examples of AI-driven analysis techniques that have allowed researchers to identify new molecular pathways, inflammatory disease subtypes and immune signatures in various types of inflammatory diseases such as tendinopathy, keloids, sepsis, COVID-19-related inflammation, fibrotic diseases and autoimmune disorders.AI-related models offer non-invasive approaches that pave the way for developing personalized or "precision" medicine.This would allow clinician to early stage accurate diagnosis with favorable treatment option.