MedCite.eu: A Multi-Signal Retrieval Architecture for Comprehensive Clinical Literature Discovery

Medical literature search systems have historically prioritized precision over recall, returning insufficient numbers of papers for comprehensive evidence synthesis. Recent independent evaluations have demonstrated that AI-powered search tools achieve only 25.5–69.2% sensitivity (mean 39.5%) compared to gold-standard systematic review methodologies, with high precision (41.8%) but poor comprehensive retrieval ability. We present MedCite.eu, a retrieval architecture explicitly designed to guarantee comprehensive literature coverage (≥10 relevant papers per query) through recall-optimized multiparallel search and multidimensional ranking. The system implements a three-stage pipeline that emphasizes broad retrieval, followed by intelligent ranking. Validation across representative clinical queries confirmed consistent retrieval. MedCite.eu returned 10–30 relevant papers for each query. The system is architecturally designed to guarantee ≥10 papers through multiparallel search. Validation across representative clinical queries confirmed consistent retrieval, with strong prioritization of recent evidence (2020+) through temporal ranking signals, compared to 15–25% in conventional precision-optimized systems that rely on historical citation counts. The architecture achieves comprehensive retrieval through a recall-first design and multiparallel search (~130 papers fetched across three streams). By prioritizing recall over precision, the system addresses the sensitivity failures documented in the independent evaluations of AI search tools.