Show HN: EBM Lens, searches biomedical papers, ranks evidence, grounds claims (github.com)

A new tool called EBM Lens has been introduced, aiming to enhance evidence discovery for biomedical queries by efficiently searching through twelve public biomedical databases and utilizing a citation graph to rank research findings by relevance and study design. It provides a synthesized overview of claims with citations, addressing common issues in literature retrieval, such as citation hallucination and varying study designs. Users can run searches through a read-only demo, allowing for quick access without any need for accounts or complex setups. This development is significant for the AI/ML community as it combines advanced capabilities of large language models (LLMs) with biomedical research retrieval techniques, empowering researchers to navigate vast amounts of information effectively. The pipeline employs a multi-round search loop, refining queries based on the literature's vocabulary, and ensures that only appraised sources are presented. The tool emphasizes grounding in evidence and highlights conflicts in studies, presenting a more nuanced view of scientific claims, making it particularly valuable in evidence-based medicine scenarios. Technical aspects include the use of simultaneous queries to multiple data providers and advanced ranking mechanisms that can differentiate between study designs to better inform clinical decisions.