SatIR: Scalable High-Recall Constraint-Satisfaction-Based Information Retrieval for Clinical Trials Matching
Researchers have developed SatIR, a novel retrieval system designed to improve the matching of patients to clinical trials. This system goes beyond simple semantic similarity by treating trial eligibility criteria as formal constraints that must be satisfied. SatIR integrates Satisfiability Modulo Theories (SMT), relational algebra, medical ontologies, and LLMs to convert complex clinical information into executable constraints, enabling more accurate and efficient trial matching. AI
IMPACT This approach could significantly improve patient access to relevant clinical trials by overcoming limitations of traditional similarity-based search.