Importance The months after psychiatric hospital discharge are a time of high risk for suicide.
Intensive postdischarge case management, although potentially effective in suicide …

The modern pathology laboratory serves to provide timely and reliable pathologic
examination of tissue and liquid-based specimens from a variety of patient types and …

Growing evidence has shown that applying machine learning models to large clinical data
sources may exceed clinician performance in suicide risk stratification. However, many …

Background In the global effort to prevent death by suicide, many academic medical
institutions are implementing natural language processing (NLP) approaches to detect …

Importance Hepatocellular carcinoma (HCC) and its mortality are on the rise. Viral hepatitis
and alcohol are leading risk factors; however, other risk factors among veterans are less …

Statistics Extraction and Integration from unstructured EHRs pose a giant venture in
healthcare. Unstructured EHRs derive much of their cost from the substantial amounts of …

Traditional research methods have shown low predictive value for suicidal risk assessments
and limitations to be applied in clinical practice. The authors sought to evaluate natural …

In the machine learning subfield of natural language processing, a topic model is a type of
unsupervised method that is used to uncover abstract topics within a corpus of text. Dynamic …

Background: Suicide risk prediction models frequently rely on structured electronic health
record (EHR) data, including patient demographics and health care usage variables …

Bakgrunn: Bruk av kunstig intelligens (AI) har et stadig økende fokus, også i helsevesenet.
En metode som virker lovende, er naturlig språkprosessering (NLP), som kan brukes til …