Combining SciBite’s established industry-leading ontology-based semantics with machine learning (ML), the award-winning semantic technology company, SciBite launches SciBiteAI and boasts its offerings. Because the capabilities offered are far off the expectations you may set from other AI solutions.
SciBiteAI’s architecture, Designed to remove the need to write complicated code, ensures it is readily deployable for applications. Being customizable for scientific text makes it perfect for use in the life sciences, often a weakness of more generic tools.
The guiding goals behind the launch of SciBiteAI were to enable scientists, researchers, and application developers (novice ML enthusiasts) to use semantics-based deep learning and replace complex coding with standardized REST APIs ready for integration into business workflows and software. The motivation to enhance the understanding of scientific content by Combining SciBite’s expertise in semantics and FAIR data to develop machine learning-based solutions turned into another guiding goal for the company.
The above goals were set up to design SciBiteAI to meet critical needs for the life sciences. Created using state-of-the-art deep learning language models and trained with data leveraging SciBite’s industry-leading semantic technology and curation, the platform has a wide variety of functions to offer. Some of which are :
- Identification of concepts not covered by existing vocabularies or ontologies by Language comprehension based Named Entity Recognition (NER);
- Improved disambiguation and term discovery by integrating with SciBite’s TERMite NER software to
- Identification of complex relationships between concepts such as adverse events and drugs, diseases and genes;
- Identification of the parts of the text which answer natural language questions.
Here is what SciBite’s CTO, James Malone, has to say in this regard: “SciBiteAI represents the next generation in our ability to understand and analyze scientific text,”
He also added that the software now exploits and helps build our life science ontologies and find novel and relevant data relationships. With SciBiteAI, the company plans to offer a complete solution from managing core data standards to advanced AI-based discovery.