ConceptualEyes in Medical Research

July 1, 2017 at 1:28 am  | 
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With 25 million medically-relevant publications since 1865 and 2 million more being added every year, ConceptualEyes deals with the following Big Data challenges for medical research– (i) the need to store, retrieve, parse and reason with the massive body of knowledge, (ii) the need to curate and deal with datasets where there is more noise than signal, (iii) the computational complexity of dealing with hierarchies and semantic relationships while interpreting natural language, (iv) designing and applying algorithms that scale on modern compute architectures to provide interactivity for discovery.

ConceptualEyes is helping researchers “connect the dots” across predications provided in MEDLINE from the National Library of Medicine, allows a medical expert to explore non-obvious clinical associations with semantic meaning and generate a significance score of belief for a “hypothesized” association. ConceptualEyes is able to conduct searches based on numerous information foraging heuristics on 91 million medical assertions in the order of a few seconds rather than the years it would take to manually perform this search over the entire body of knowledge.

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