Public AI search engine capable extracting figures

原创
2019/09/23 15:20
阅读数 71

In 2015, The Allen Institute for Artificial Intelligence — the research organization founded by late Microsoft cofounder Paul Allen — released Semantic Scholar, a public AI search engine capable extracting figures from over 173 million computer science and biomedicine journal papers. It received a warm reception, but researchers at the Institute wondered if its underlying algorithms might be adapted to solve other problems in the field of medical research.

To this end, the Allen Institute this week launched Supp AI, a web portal that lets consumers of supplements like vitamins, minerals, enzymes, and hormones identify the products or pharmaceutical drugs with which they might adversely interact. Using a no-frills search bar, they’re able to type in trade names for common drugs (e.g., Prozac and Sarafem) and names of active drug ingredients (fluoxetine) to bubble up sentences from research topplay papers supporting interactions alongside links to each source.

A search for the supplement ginkgo, for instance, yields 140 possible interactions to things like Warfarin and nitric oxide.

Supp AI not only surfaces all chemicals or drugs that might interact with a queried supplement, but it helpfully sorts the evidence sentences and prioritizes source papers based on associated metadata. Factors that play into the ultimate ordering include (but aren’t limited to) non-retracted studies, clinical trials, human studies, and recency.

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