SOMA is a research automation platform designed to efficiently uncover undocumented pathways between factors and medical conditions using a database of open access journals. It leverages AI technology to build a knowledge graph, speeding up the search process. The platform analyzes medical research articles, extracts important concepts, and identifies causal and associative relationships between them. This information is organized into a specialized database, allowing researchers to specify a pair of concepts and retrieve causal chains documented by sentences extracted from research articles.
AI-powered research platform for uncovering connections between factors and medical conditions.
- Accelerating medical innovation by identifying hidden connections between factors and medical conditions.
- Enhancing literature reviews by uncovering relevant articles based on mechanisms of action.
- Saving time on organizing reviews and focusing on core research activities.
- Researchers can specify a pair of concepts (cause and effect) and the system will retrieve causal chains with lengths specified by the filter. Every link in each causal chain is documented by a sentence extracted from a research article. Specific research articles can be accessed by the user using web links provided by the system.
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