Articles tagged: NLP (Natural Language Processing)

  1. How SciBite Technology Can Facilitate Gene-Disease Relationship Extraction

    As genomic sequencing technologies get more advanced, large numbers of gene-disease associations have emerged. A gene with an unclear role within a disease is a source of ambiguity and can lead to misdiagnosis. In this blog, we demonstrate how semantic search technology can facilitate Gene-Disease Relationship Extraction.

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  2. SciBite launches SaaS Versions of its Semantic Technology Products

    SciBite has today unveiled its new Software-as-a-Service (SaaS) version of TERMite, SciBite’s named entity recognition engine, and its CENtree™ ontology management system.

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  3. Exploring Breast Cancer Biomarkers with a Literature Biomarker Database

    In this piece we'll show how natural language processing can be applied to build a searchable database of disease biomarkers, presented in the context of their corresponding scientific publications. To illustrate the power of this approach we'll focus on examples of protein biomarkers relating to Breast Cancer.

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  4. Unlocking insight from scientific literature in under-supported languages through Machine Learning approaches

    In this blog, we delve into how we applied novel machine learning and curation methods to Japanese language literature, techniques we believe are transferable to other under-supported languages.

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  5. Talking to TERMite – introducing the SciBite scripting suite

    We’re pleased to announce that we’ve given our TERMite Toolkit an update, including updating our Python Toolkit. We’re also excited to introduce our new R module. Read more in this blog post.

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  6. A helping hand from BioBERT for Deep Learning approaches

    SciBite CSO and Founder Lee Harland shares his views on the use of BERT (or more specifically BioBERT) for deep learning approaches.

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  7. The benefits of Semantically Enriching document mining for Chemists

    In this blog post, learn more about how our partner ChemAxon have integrated SciBite’s ultrafast named entity recognition (NER) and extraction engine solution, TERMite, into their leading cheminformatics platform, and how this can benefit your organisations informatics architecture.

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  8. SciBite releases new version of ultra-fast term identification, tagging & extraction engine – TERMite 6.3

    SciBite releases a new version of industry leading, ultra-fast named entity recognition (NER) and extraction engine, TERMite 6.3, which delivers a range of new enhancements, including simplified connectivity to third party systems.

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  9. SciBite & RDF (Resource Description Framework) – A natural semantic fit

    In this article, we’ll explore how SciBite’s platform works with the semantic web and its primary data representation format, RDF, along with the benefits each technology brings.

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  10. Climbing Mt Peer Review: May AI help you with that?

    At every stage of a researcher’s career, literary reviews are an integral part of scientific investigation. They help to ensure researchers are aware of the current landscape, latest findings and newest technologies in their field.

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  11. SciBite technology transforms Data Mining & Horizon Scanning

    With 6,800 new scientific publications released every day (one every 12 seconds) data mining and horizon scanning is becoming increasingly difficult for medical researchers, which can lead to delayed discoveries in the life science space.

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  12. Named Entity “Un-Recognition”

    How do you automate redaction of personal and sensitive data?

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  13. Drug Repurposing, Rare Diseases and Semantic Analytics

    In this blog we cover how to look potentially reduce the cost of and speed up the repurposing pipeline.

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  14. Taking Semantic Search to Full Text

    Guest post from CCC, leader in creating global licensing and full content solutions, on the advantage of full text for semantic search.

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  15. TERMite 6.1 release

    Announcing the latest release of SciBite's semantic engine, TERMite 6.1.

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  16. SciBite and PerkinElmer Provide Advanced Analytics from Unstructured Scientific Data

    PerkinElmer, Inc., today announced sophisticated scientific semantic enhancements to the PerkinElmer Signals™ Perspectives platform, powered by SciBite and Attivio.®

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  17. Fuzzy matching now in TERMite

    In the latest release of TERMite, we now include a fuzzy matching feature to help identify incorrectly spelt concepts in text.

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  18. TERMite v5.9 now available

    Announcing the latest version of our flagship text analytics software for life sciences, TERMite 5.9.

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  19. Semantically-Powered Social Collaboration

    How do you know what your colleagues sat opposite you are working on? How about those in another office/building/site? More importantly, do you know who would be the expert on any particular topic within your company?

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  20. The Evolution of Data

    Over the 50 years how we collect and play music has changed dramatically from physical copies on Vinyl through to electronic mp3s. Each new technology often requires a new device and format to play yet it is still essentially just music.

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  21. Semantics in Enterprise Search

    Enterprise Search, a complex challenge in extracting accurate results from the ever-increasing volumes and variability of big data. But, and it’s a big but, how does a search system know what to look for?

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  22. Loving the Data Others Don’t

    Like it or loathe it, plain text is a goldmine of information. The challenge is that data mining is often complicated through ambiguity. Sure, identifying, disambiguating and extracting those scientific terms is a big challenge but we’ve got it covered.

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