Using Machine Learning (ML) and Natural Language Understanding (Nlu) To Better Understand Patient Populations

This session will discuss how Realyze Intelligence is enabling health care organizations to know their patients better by applying a combination of clinical knowledge and Machine Learning (ML). This unique solution unlocks information from across the entire patient chart, including interpreting the unstructured narrative documentation. Unlike traditional ML solutions, however, Realyze uses a next-generation clinical Natural Language Understanding (NLU) that not only extracts data from the narrative text, but also the clinical meaning of the text – just as a clinician would. The solution can then reuse this understanding and clinical evidence for many purposes. During this session, we will discuss how the solution is being used today. For example, identifying CKD patients progressing towards ESRD, prioritizing patients for COVID response based on social determinants of health (SDoH), clinical research and trial matching, improving registry abstraction, identification of proper goals of care documentation, and much more.