Abstract: Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS) pose diagnostic challenges due to their variable clinical manifestations and the fluctuating nature of relevant biomarkers. This presentation introduces an innovative approach using artificial intelligence (AI) to analyze a comprehensive set of biomarkers—including blood counts, metabolic panels, and specific autoimmune responses like ASO and the Cunningham Panel. By leveraging machine learning techniques, our AI model identifies complex biomarker patterns that correlate with PANDAS, offering a more definitive diagnostic tool. This method not only enhances diagnostic precision but also sets the stage for personalized treatment strategies, potentially transforming care for affected children. Our approach promises more objective, reliable, and rapid diagnostics, facilitating timely and effective interventions.
December 28, 2025