Dietary Self-Management Using Mobile Health Technology for Adults With Type 2 Diabetes: A Scoping Review.

Objective: Dietary self-management is one key component to achieve optimal glycemic control. Advances in mobile health (mHealth) technology have reduced the burden of diabetes self-management; however, limited evidence has been known regarding the status of the current body of research using mHealth technology for dietary management for adults with type 2 diabetes.

Methods: Literature searches were conducted electronically using PubMed, CINAHL (EBSCO), Web of Science Core Collection, PsycINFO (Ovid), EMBASE (Ovid), and Scopus.

Identifying Patients With Hypoglycemia Using Natural Language Processing: Systematic Literature Review.

Background: Accurately identifying patients with hypoglycemia is key to preventing adverse events and mortality. Natural language processing (NLP), a form of artificial intelligence, uses computational algorithms to extract information from text data. NLP is a scalable, efficient, and quick method to extract hypoglycemia-related information when using electronic health record data sources from a large population.