The process of de-identifying protected health information (PHI) from unstructured medical notes is often essential when working with patient-level documents, such as physician notes. Using current state-of-the-art techniques, automated de-identification of both structured and free-text medical text can be accomplished at the same level of accuracy as with human experts. Recently, John Snow Labs’ Healthcare Natural Language Processing (N...

In this Webinar, Juan Martinez from John Snow Labs and Ken Puffer from ePlus will share lessons learned from recent AI, ML, and NLP projects that have been successfully built & deployed in US hospital systems: Improving patient flow forecasting at Kaiser Permanente A real-time clinical decision support platform for Psychiatry and Oncology at Mount Sinai Automated de-identification of 700 million patient notes at Providence Health Then the...