Hi, I'm Jeff Saffer. And I'm Vicki Burnett. We are the founders of Quertle and the architects of first big data artificial intelligence platform for discovering hidden insights from the biomedical literature.
At some point, all of us have been frustrated by not finding the information you need. But it is more than frustration; a European Patent Office study showed that up to 30% of R&D money is wasted rediscovering existing information. And, according to the NIH, one of the leading causes for grant proposal failure is proposing work that isn't actually new. Clearly more advanced methods are required to find value in the overwhelming tsunami of biomedical information.
Hence, we created our BioAI™ platform and the Qinsight™ discovery product. BioAI was specifically created to address unique issues encountered with the biomedical and biological sciences. It uses
With its artificial intelligence underpinnings, Qinsight™ provides
In our first example using Qinsight™, we are looking for a connection between nitric oxide and disease. Unlike with other products, with Qinsight™, you can search for nitric oxide, NO as we are doing here, or other synonyms - and rest assured that you will find all the related terms and the different forms of nitric oxide. This AI-aided recognition is CRITICAL since 20% of the literature about nitric oxide uses only NO and thus cannot be found by other systems that ignore NO or treat it as no (the negative) or NO (meaning number), and so on. Can you afford to overlook these potentially critical references?
In this example , we are also using one of our unique Power Terms, which will search for actual diseases and not clutter the results with hits from the generic terms "disease", "syndrome", etc. You do not want important documents to get lost in a sea of noise. In this search, we are finding actual diseases such as asthma.
Qinsight™'s artificial intelligence not only does a better job of discovering concepts, but also immediately focuses on relevant documents, so you don't have extraneous results to weed through. Qinsight™ actually discovers the meaning of the documents, as they relate to your query, to provide highly precise information. Keyword searching simply cannot do that. Qinsight™'s modern methods are applied to about 40 million documents, with full-text searching for more than 10 million of the documents. And we can include your own licensed content securely within a custom deployment.
Not only do you need relevant results, from the right content, but you also need intuitive ways to explore those results. Along with several self-explanatory filters, Qinsight™ is the only solution that offers a unique Negative Statement filter. This allows you to exclude results where the author explicitly said nitric oxide and a disease were not connected, or to focus on such negative associations. Thus, you can understand why your search terms are connected in some instances but not others.
Another unique capability in Qinsight™ is the AI-powered identification of concepts related to your query. Importantly, this is much more powerful and relevant than showing you concepts that appear somewhere in the results documents. For our current example, you can see the different concepts related to nitric oxide. And because we used the Diseases Power Term, we also get specific answers to the question "what diseases are connected to nitric oxide". Key Concepts allow you to follow up on lines of thought you knew about, and to recognize new concepts that you didn't think about. Just click on any Key Concept to limit the results accordingly. The Key Concepts are essentially a summary of why the results documents are important to you.
The Concept Cloud makes this summarization even easier.
Now, you can see the relative influence of each concept in relating the results to your query. Each concept in the Cloud is clickable so that you can immediately see the underlying documents.
With Key Concepts, although you may focus on the more common terms, the literature is dynamic, and less common concepts may be growing in importance. Quertle's Concept Trends visualization uses artificial intelligence to uncover trends that are specifically related to your query.
The Concept Trends visualization provides a spiral clustering of the Key Concepts, with the size of each bubble reflecting the overall importance of that concept to your query. In addition, you'll see that some concepts have a red border. This indicates an increasing trend for those concepts. We have hovered over one of these concepts, and see that Insulin Resistance is growing in importance with regard to its association with Nitric Oxide. A blue border indicates a decreasing trend.
In the second example, we are interested in the genetic contributions to melanoma. Although many genes have been identified, it is difficult to understand, from a list, the interplay among these genes - an important consideration. The Concept Connections visualization uses artificial intelligence to tease out these connections.
We are now looking at a portion of the Concept Connections. The connections are now obvious, with darker cells indicating a more significant connection, such as the one between GNAQ and KIT. Importantly, this is NOT a simple co-occurrence matrix. Rather the system is determining the significance specifically as relevant to your query. This provides confidence that the connections are important to your line of investigation.
We have only touched on some of the features and value of Qinsight™, and want to end with a note that there is much more. Qinsight™ can fit into your workflows. And, we can customize Qinsight™ for your needs (try that with the other "solutions").
There is a reason we call it Q INSIGHT™! Please contact us for more information. Thank you.
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