Much of the knowledge and information needed for enabling high-quality clinical research is
stored in free-text format. Natural language processing (NLP) has been used to extract …

Background In the last decade, long-tail learning has become a popular research focus in
deep learning applications in medicine. However, no scientometric reports have provided a …

Background Delirium is an acute neurocognitive disorder that affects up to half of older
hospitalized medical patients and can lead to dementia, longer hospital stays, increased …

Objective This paper evaluates the application of a natural language processing (NLP)
model for extracting clinical text referring to interpersonal violence using electronic health …

Background Computational text phenotyping is the practice of identifying patients with
certain disorders and traits from clinical notes. Rare diseases are challenging to be …

Background: Suicide is a growing global public health problem that has resulted in an
increase in the demand for psychological services to address mental health issues. It is …

Objective Pituitary adenomas are the most common type of pituitary disorders, which usually
occur in young adults and often affect the patient's physical development, labor capacity and …

Background Better phenotyping of routinely collected coded data would be useful for
research and health improvement. For example, the precision of coded data for hemorrhagic …

Computational text phenotyping is the practice of identifying patients with certain disorders
and traits from clinical notes. Rare diseases are challenging to be identified due to few …

The everyday consumption of household goods is a significant source of environmental
pollution. The increase of online shopping affords an opportunity to provide consumers with …