Background: The process of documentation in electronic health records (EHRs) is known to
be time consuming, inefficient, and cumbersome. The use of dictation coupled with manual …

Background: Clinical natural language processing (cNLP) systems are of crucial importance
due to their increasing capability in extracting clinically important information from free text …

Experts have noted a concerning gap between clinical natural language processing (NLP)
research and real-world applications, such as clinical decision support. To help address this …

Background Patient-generated health data (PGHD) captured via smart devices or digital
health technologies can reflect an individual health journey. PGHD enables tracking and …

Background: As more health care organizations transition to using electronic health record
(EHR) systems, it is important for these organizations to maximize the secondary use of their …

Background: The growing interest in observational trials using patient data from electronic
medical records poses challenges to both efficiency and quality of clinical data collection …

With the rapid growth of information technology, the necessity for processing substantial
amounts of health data using advanced information technologies is increasing. A large …

Background Although electronic health records (EHRs) have been widely used in secondary
assessments, clinical documents are relatively less utilized owing to the lack of standardized …

The capabilities of natural language processing (NLP) methods have expanded significantly
in recent years, and progress has been particularly driven by advances in data science and …

Background: Medical terms are a major obstacle for patients to comprehend their electronic
health record (EHR) notes. Clinical natural language processing (NLP) systems that link …