John Snow Labs
recently announced that it has launched its natural language processing (NLP) library with healthcare-specific deep learning models to help developers create software applications that understand medical texts.
The NLP library will give healthcare providers the ability to quickly process and interpret a variety of clinical texts like patient notes, lab reports, clinical trial results, medical research and chatbot and clinical discussions. Healthcare professionals can then use the analysis to determine which patients are at risk, match patients to clinical trials, alert caregivers about patient safety, make clinical recommendations or automate clinical coding and billing.
IBM Watson has a similar system in place that can interpret genetic testing results faster and with more efficiency than manual testing. It also identifies novel drug targets and new indications for existing drugs, can support government agencies in their work and helps clinicians spend less time searching literature and more time caring for oncology patients.
Healthcare data scientists can put new deep learning models in the John Snow Labs’ open source NLP Library for Apache Spark, which the company claims is 80 times faster than on spaCy. Healthcare organizations can also license the new models with an annual subscription to include access to regular updates related to the latest biomedical research and terminology.
Kaiser Permanente is using John Snow Labs’s open source NLP library to better predict the demand for hospital beds in the future to make sure that there will be enough nurses to take care of incoming patients at one of its hospitals.
“We’re excited to provide new state of the art models that will accelerate many healthcare AI projects. Training domain-specific NLP models is hard, and teams often compromise because they don’t have the skills or the time. Now the most advanced research is productized and easily available out of the box,” said Saif Addin Ellafi, John Snow Labs product manager.
