Head-to-Head Evaluation of the Cancer Ontology Supervised Multimodal Orchestration (COSMO) AI System Versus Pathologist-Only Review

This study evaluates the diagnostic performance of the Cancer Ontology Supervised Multimodal Orchestration (COSMO) AI system for cancer subtype classification and compares it head-to-head with pathologist-only review. Pathologists will independently review de-identified whole-slide images derived from up to 300 patients across three anatomical sites (brain, lung, kidney) and provide diagnostic assessments. In parallel, COSMO will process the same cases offline to generate independent predictions, enabling direct comparison of diagnostic accuracy between human experts and the AI system. The study will characterize the diagnostic accuracy of COSMO and pathologists, inter-observer agreement, and variations in performance across anatomical sites and cancer types with different incidence rates. Results will establish how COSMO compares to pathologists on identical cases and will inform the development of AI-assisted diagnostic systems in clinical practice.