Knowledge Graph Boosts AI Extraction of Drug Side Effects from Patient Narratives
GraphRAG-ADR combines a knowledge graph with a large language model to extract adverse drug reactions from informal patient narratives, reaching ...
GraphRAG-ADR combines a knowledge graph with a large language model to extract adverse drug reactions from informal patient narratives, reaching ...
A re-analysis of FDA adverse event data from 2014 to 2024 finds that only 11.2% of the rise in serious ...
A retrospective cohort of 332 treatment-experienced adults with HIV at a Nigerian hospital found that nearly half experienced at least ...
A multi-phase Nature Cancer study found that an agentic AI system detected immune-related adverse events in clinical notes with retrospective ...
A FAERS analysis of 2,630 case reports found toremifene carried the strongest hepatobiliary adverse-event reporting signal among seven endocrine therapies ...
A subject-level analysis of 91 placebo-controlled trials covering nearly 108,000 participants found no increased risk of suicidal ideation or behavior ...
A survey of 152 final-year dentistry students at Ajman University found positive attitudes toward pharmacovigilance but limited knowledge and low ...
A new Perspective proposes a minimal framework for documenting symptom trajectories, context, and actions in individual case safety reports, with ...
A disproportionality analysis of Japan's JADER database found disproportionate acute kidney injury reporting signals for sacubitril/valsartan, with heart failure and ...
An automated reporting tool embedded in two Sydney hospitals' electronic medical records increased adverse drug reaction reports to Australia's regulator ...
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© 2026 Scienmag - Science Magazine