How do we extract and link relationships from scientific research?
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We extract relationships from scientific research by using large language models (LLMs) to scan studies and pull out each of the components reported (i.e., variables, and the following as available: mechanism type, statistic type, statistic value, confidence interval, and p-value). For every extraction, traceability to the original source is preserved by storing all data at the highest resolution, true-to-source, along with links to the underlying sources, which are provided to users.
Once extracted, we link findings together by mapping each of the variables in a relationship to a higher-level concept or topic grounded in external ontologies such as MESH, ICD-10, SNOMED CT, and DSM-5, LNC, and Wikidata. For example, a variable named “daily aspirin usage” would be assigned to the topic of “Aspirin” [MESH ID: , Wikidata ID: ], and thus discoverable by searching for that associated topic. The result is an up-to-date and interoperable graph of evidence-based findings.
