mindtalks artificial intelligence: SciBiteAI Launched to Intelligently Guide Life Sciences Organizations – AiThority – picked by mindtalks

SciBite , the award-winning semantic technology business enterprise, announced the launch of SciBiteAI.

SciBiteAI is a state-of-the-art Artificial Intelligence software platform for leveraging machine learning models alongside semantic technology to unlock insights into Life Sciences data.

Just what exactly SciBiteAI Offers?

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SciBiteAI offers unique competencies beyond the plethora of different AI solutions in the marketplace by combining machine learning having SciBite’s established industry-leading ontology-based semantics. The combined AI ML choices enables customers to unlock remarks hidden in the mountain from life science text.

In the modern context for Deep Learning applications, SciBiteAI has already been manufactured to meet key desires for the life sciences utilizing three guiding goals:

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  1. To enable scientists, scientists, and application developers make use of semantics-based deep learning without having to end up machine learning experts;
  2. To restore complex coding with standardized REST APIs, ready for integration into business workflows and application;
  3. Combine SciBite’s expertise in semantics and FAIR information to develop machine learning-based options that enhance the perception of exact content.

SciBiteAI was created using state-of-the-art full learning language models, trained by using data leveraging SciBite’s industry-leading semantic technology and curation. The platform comes with a wide variety of characteristics, including:

  • Vocabulary comprehension based Named Entity Detection (NER) to identify concepts in no way covered by existing vocabularies or even ontologies;
  • Integration with SciBite’s TERMite NER software to enhance disambiguation and term discovery;
  • Relationship Identification: Identify sophisticated relationships between concepts such just as drugs and adverse events, family genes and diseases;
  • Q& A: identifying parts of typically the text which answer natural dialect questions.

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“SciBiteAI consists of the next generation in all of our capability to understand and analyze methodical text, ” says SciBite CTO, James Malone . “Our software nowadays exploits and helps build your life science ontologies, as well as find novel and applicable relationships within data. With SciBiteAI we offer a complete substitute from managing core data expectations to advanced AI-based discovery. ”

SciBiteAI’s architecture is without a doubt designed to take away the need in order to write complicated code, ensuring this is readily deployable for software. The solution is also personalized for scientific text, ensuring this is optimized use with the personal life sciences, often a weakness for more generic tools.

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