Machine learning Archives

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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SciBite AI 2.0: Combine deep learning models with powerful semantic algorithms

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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A de novo vocabulary approach for producing Machine Learning models (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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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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SciBite 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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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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Annotation of the Covid-19 open research dataset for the scientific research community

In this blog find out how the SciBite team has responded to the tech community call to arms from The White House after they released an Open Research Dataset (CORD-19), with the hope to help uncover insights and answer high-priority scientific questions related to Covid-19.
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Launch of 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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Machine Learning insights from Japanese language academic text

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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The 12 days of Machine Learning tips for creating labelled training data

On the first day of Christmas SciBite gave to me... 12 top tips for creating labelled Machine Learning training data.
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Semantic approach to training ML data sets using ontologies & not Sherlock Holmes

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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Building the future of text analytics

SciBite CSO and Founder Lee Harland features in KM World Magazine, where he talks about 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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A helping hand from BERT 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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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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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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Why simplifying visualization 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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The benefits of centralizing 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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How the use of Machine Learning can augment adverse event detection

When it comes to identifying adverse events (AEs), things are not always as they seem. Consider a paper describing a new treatment for a given illness - how can we determine which adverse event terms refer to actual adverse events as opposed to symptoms of the illness itself, given that those terms may be identical? Is this new drug treating arrhythmias or causing them, for example?
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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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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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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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Of Burns and Bums: Machine Learning surprises!

As many of our regular visitors will know, the focus of our work here at SciBite is unlocking the knowledge held in the vast amount of biomedical text researchers have access to. Sometimes this yields well, interesting, results...
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Machine Learning and phenotype triangulation

Disease detective part 3:
In our final disease detective article, we’ll take Part 2’s topic a little further and zoom in on how we can find new relationships between diseases where direct evidence is sparse.
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