Articles tagged: Artificial Intelligence

  1. Detecting Adverse Drug Reactions in Social Media Posts 

    The highly informal language used in social media posts is challenging to analyse. Recognizing this need, SciBite has created a machine learning-based model capable of identifying adverse Drug Reactions associated with medications from the informal language found in social media posts.

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  2. SciBite Virtual User Group Meeting 2021: What we discovered

    SciBite, the award-winning semantic technology company, recently hosted its annual User Group Meeting virtually for the second year running. Held over three days, we brought together our customers and partners to have discussions around Ontologies and Ontology-Powered Entity Registration, FAIR data ecosystems, Data FAIRification, and Knowledge Graphs

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  3. SciBite announces the release of SciBite Search V2.0

    In this blog we announce the v2.0 release of SciBite Search, our intelligent scientific search platform. We’ve expanded our Elsevier data connectivity, broadening the sources you can load and search, as well as a host of features that improve the user experience.

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  4. Release of SciBite AI 2.0: Combine deep learning models with powerful semantic algorithms to unlock Life Science semantic data

    SciBite AI combines deep learning Artificial Intelligence models with our powerful semantic algorithms, enabling the pharmaceutical and healthcare sectors to exploit and rapidly use life science data in research and development.

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  5. De Novo Vocabulary Approach for Producing AI Models

    In this blog hear how our SciBite AI team demonstrated a de novo vocabulary approach for generating a machine learning model, allowing researchers to identify and annotate text containing mutant descriptors.

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  6. The Powerful Combination of Semantics-Based Machine Learning and Domain Expertise

    In this blog hear about SciBite's recent talk at Pistoia Alliance’s Spring Virtual Conference on semantics-based machine learning and domain expertise on a day dedicated to emerging science and technologies.

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  7. SciBite CTO joins ISB Panel to discuss AI and the Future of Biocuration

    Our SciBite CTO was invited to take part in a panel discussion as part of this year's virtual Biocuration Conference, where he shared his thoughts in a thought-provoking discussion on “The Future of Biocuration.”

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  8. SciBite launches AI-driven Semantic Search platform to help manage the Life Science data deluge

    Intelligent scientific search platform, SciBite Search, enables researchers to quickly find meaningful insights from structured and unstructured public and proprietary biomedical data.

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  9. SciBite launches SciBite AI Relationship Extraction models

    SciBite announces the release of SciBite AI Relationship Extraction models, which provide the enhanced ability to identify complex relationships within text to further unlock insights from Life Sciences data.

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  10. SciBite showcases cutting-edge technology to Life Science leaders at Virtual User Group Meeting

    Cambridge, UK – SciBite, the award-winning semantic technology company, recently hosted its first Virtual User Group Meeting across three days, bringing together its global customer base to share cutting-edge insights.

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  11. State-of-the-art Artificial Intelligence software platform for Life Sciences organisations

    SciBite announces the launch of SciBite AI, a state-of-the-art Artificial Intelligence software platform for leveraging machine learning models alongside semantic technologies to unlock insights into Life Sciences data.

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  12. A Semantic Approach to Training Machine Learning Data Sets

    SciBite's CTO explains how the semantic approach to using ontologies is essential in successfully training machine learning data sets. In this blog he discusses how Sherlock Holmes (amongst others) made an appearance when we looked to exploit the efforts of Wikipedia to identify articles relevant to the life science domain for a language model project.

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  13. Human and Machine Intelligence: Building the future of Text Analytics

    SciBite CSO and Founder Lee Harland features in KM World Magazine where he talks on the future of text analytics and how ontologies are the de facto standard to encode semantics in an understandable form for both humans and machines.

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  14. 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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  15. Ontologies with SciBite: How Ontology enrichment is essential in maintaining Clean Data

    Ontologies have become a key piece of infrastructure for organisations as they look to manage their metadata to improve the reusability and findability of their data. This is the final blog in our blog series 'Ontologies with SciBite'. Follow the blog series to learn how we've addressed the challenges associated with both consuming and developing ontologies.

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  16. Ontologies with SciBite: The importance of facilitating collaboration and integration

    Ontologies have become a key piece of infrastructure for organisations as they look to manage their metadata to improve the reusability and findability of their data. This is the third blog in our blog series 'Ontologies with SciBite'. Follow the blog series to learn how we've addressed the challenges associated with both consuming and developing ontologies.

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  17. Ontologies with SciBite: Why simplifying visualisation and curation is better for everyone

    Ontologies have become a key piece of infrastructure for organisations as they look to manage their metadata to improve the reusability and findability of their data. This is the second blog in our blog series 'Ontologies with SciBite'. Follow the blog series to learn how we've addressed the challenges associated with both consuming and developing ontologies.

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  18. Ontologies with SciBite: The benefits of centralising Ontology Management

    Ontologies have become a key piece of infrastructure for organisations as they look to manage their metadata to improve the reusability and findability of their data. This is the first blog in our blog series 'Ontologies with SciBite'. Follow the blog series to learn how we've addressed the challenges associated with both consuming and developing ontologies.

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  19. The SciBite difference – It’s all about your data

    In this blog post SciBite's CSO and Founder Lee Harland addresses a very common question we are often asked by potential customers and partners...

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  20. SciBite announced as Best of Show Award finalists for Bio-IT World 2019

    SciBite has been shortlisted for Bio-IT World 2019’s prestigious Best of Show Award.

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  21. Are Ontologies relevant in a Machine Learning-centric world?

    SciBite CSO and Founder Lee Harland shares his views on why ontologies are relevant in a machine learning-centric world and are essential to help "clean up" scientific data in the Life Sciences industry.

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  22. 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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  23. Power to the patients: An AI-based microbiome analyser to support IBD patients from the comfort of their own homes

    The work presented here describes the winning entry to a challenge set by ARM, Atos and Cavium at the Wellcome Genome Campus Hackathon 2018.

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  24. Text-mining drug labels for genetic factors influencing efficacy and safety to support clinicians at the point of prescription

    Only 50-75% patients respond beneficially to first-line drug therapy, causing unnecessary costs to healthcare providers and, more importantly, adversely impacting a patient’s quality of life.

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  25. 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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