John Snow Labs Announces State-of-the-Art Enhancements to its Spark...

John Snow Labs Announces State-of-the-Art Enhancements to its Spark NLP Technology, Resulting in 2.5M Downloads and 9x Growth in 2020

By Healthcare Tech Outlook | Friday, January 08, 2021

Spark NLP ranked by data scientists as the most popular and accurate NLP solution on the market, used by 54% of healthcare organizations

LEWES, Del. - John Snow Labs, the AI and NLP for healthcare company and developer of the Spark NLP library, today announced that it has crossed the 2.5 million download mark, experiencing 9x growth of its Spark NLP technology since January 2020. Used by 54% of healthcare organizations, Spark NLP has secured the spot as the worlds most widely used natural language processing (NLP) library in the enterprise, after only four years on the market. This rapid growth can be attributed to a long series of enhancements made to Spark NLPs state-of-the-art library, which now comes with more than 300 production-grade pre-trained models and pipelines, used by leading healthcare and life sciences companies.

John Snow Labs released 26 new versions of Spark NLP in 2019 and another 26 in 2020, with the most recent being Spark NLP for Healthcare 2.7. The most significant feature in this latest release is Text to SQL, and other upgrades include more accurate entity resolution and clinical named entity recognizers, new PICO classifier for evidence-based medicine, new biomedical named entity recognizers, and new clinical and traffic accident NER models in German. These models are pre-trained with clinical BioBERT based embeddings, the most powerful contextual language model in the clinical domain today, making it an easy-to-use, best-in-class solution for healthcare NLP projects.

This news comes on the heels of John Snow Labs release of its new named entity recognition (NER) model and classifier for Adverse Drug Events (ADE), announced in October. While the ADE NER model helps extract ADE and drug entities from a given text, the new ADE Classifier is trained on various ADE datasets, including academic texts, social media, and clinical notes. By combining ADE NER and Classifier, pre-trained pipelines are already fitted using certain annotators and transformers according to various use cases, saving users from building it from scratch.

The enhancements to Spark NLP for Healthcare beat state-of-the-art benchmarks in relation extraction, named entity recognition, and adverse event detection, and are successfully being used now by leading healthcare and life science companies, said David Talby, CTO at John Snow Labs. We are humbled by the rapid growth of our community, and expect to continue on this trajectory as we improve our NLP technology even further in the new year.

Not only is John Snow Labs committed to improving how companies from Kaiser Permanente to Roche realize the value of AI and NLP, but also providing education and resources to help further NLP knowledge and adoption. In addition to hosting the first-everNLP Summit in October, the company, in partnership with Gradient Flow, issued new research exploring the state of NLP in 2020. The research found that Spark NLP was cited as the most popular NLP library across all industries, with more than half of healthcare-affiliated respondents indicating this is what their organization currently uses. In response to this, John Snow Labs will host the first NLP for Healthcare Summit, being held from April 6-9.

Weekly Brief