Since 2010, substantial progress has been made in artificial intelligence (AI) and its
application to medicine. AI is explored in gastroenterology for endoscopic analysis of …

Background Research on the integration of artificial intelligence (AI) into community-based
primary health care (CBPHC) has highlighted several advantages and disadvantages in …

Background Concept extraction, a subdomain of natural language processing (NLP) with a
focus on extracting concepts of interest, has been adopted to computationally extract clinical …

Electronic health records (EHRs) are becoming a vital source of data for healthcare quality
improvement, research, and operations. However, much of the most valuable information …

Background Free-text descriptions in electronic health records (EHRs) can be of interest for
clinical research and care optimization. However, free text cannot be readily interpreted by a …

Background Extracting information from free texts using natural language processing (NLP)
can save time and reduce the hassle of manually extracting large quantities of data from …

Artificial intelligence (AI) technology has made leaps and bounds since its invention. AI
technology can be subdivided into many technologies such as machine learning and deep …

Ischemic stroke is a major cause of death and disability in adulthood worldwide. Because it
has highly heterogeneous phenotypes, phenotyping of ischemic stroke is an essential task …

As healthcare systems around the world face challenges such as escalating costs, limited
access, and growing demand for personalized care, artificial intelligence (AI) is emerging as …

Statistical modeling of outcomes based on a patient's presenting symptoms
(symptomatology) can help deliver high quality care and allocate essential resources, which …