Elute Intelligence launches dedicated COVID-19 Document Reader to help scientists find vital research more rapidly
Elute Intelligence Holdings (“Elute”) today announces it has launched a dedicated free-to-use online COVID-19 Document Reader to help scientists worldwide tackling the disease to find vital research more rapidly.
The COVID-19 Document Reader draws on Elute’s novel advanced software tools to intelligently search large and complex databases to identify relevant information swiftly and effectively. It is available at https://elute.info.
The databases being used include a subset of PubMed, an online resource of more than 30 million citations for papers drawn from Medline, life science journals, books and other sources. Researchers will be able to search this for articles mentioning terms related to the current COVID-19 outbreak, such as coronavirus, COVID, MERS, or SARS. Elute is proactively working with researchers to identify additional datasets.
Elute’s artificial intelligence searches, compares and analyses documents to identify similarities between them by mimicking the way people read. Researchers enter an entire paper already identified as of interest to find other relevant research. They can also create their own documents defining their own interests to enter into the Document Reader to refine searches still further.
This means the approach is very different to conventional keyword or Boolean search technologies. A patent application has been filed to protect developments of the technology.
Elute is already talking to a number of partners to support and publicise the COVID-19 Document Reader.
Peter Fischer, Chief Executive Officer of Elute Intelligence, said: “We are proud to be supporting the global fight against COVID-19 by exploiting our unique capability in document search to support scientists in their crucial research.”
Matthew White, Chief Commercialisation Officer of Frontier IP Group, said: “The COVID-19 Document Reader demonstrates just some of Elute’s ability to rapidly identify relevant information in unstructured datasets. It is great to see the team deploy this capability in such a short space of time.”