Background This study demonstrates clinical named entity recognition (NER) methods on
the clinical texts of rheumatism patients in South Korea. Despite the recent increase in the …

Abstract Information extraction systems and techniques have been largely used to deal with
the increasing amount of unstructured data available nowadays. Time is among the different …

Background: South Korea joined SNOMED International as the 39th member country. To
ensure semantic interoperability, South Korea introduced SNOMED CT (Systemized …

Objective We aimed to evaluate the validity of an algorithm to classify diagnoses according
to the appropriateness of outpatient antibiotic use in the context of Chinese free text. Setting …

HealthNet (HN) is a social network that brings together patients with similar health
conditions. HN helps users in finding a solution to their health problems by suggesting …

Unstructured data in electronic health records, represented by clinical texts, are a vast
source of healthcare information because they describe a patient's journey, including clinical …

Purpose The predictive value of suicide risk assessment in secondary mental healthcare
remains unclear. This study aimed to investigate the extent to which clinical risk assessment …

Technology and computation have changed the backdrop of various aspects of our fast-
paced lives. Healthcare is one such aspect that has been affected by this change and faces …

Background Integration of electronic health records (EHRs) data across sites and access to
that data remain limited. Objective We developed an EHR-based pediatric inpatient …

Objective Our objective was to develop a machine learning-based system to determine the
severity of Positive Valance symptoms for a patient, based on information included in their …