AI Medical Compendium Journal:
Journal of the American Medical Informatics Association : JAMIA

Showing 41 to 50 of 493 articles

Comparison of a semi-automatic annotation tool and a natural language processing application for the generation of clinical statement entries.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND AND OBJECTIVE: Electronic medical records with encoded entries should enhance the semantic interoperability of document exchange. However, it remains a challenge to encode the narrative concept and to transform the coded concepts into a st...

A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Venous thromboembolisms (VTEs), which include deep vein thrombosis (DVT) and pulmonary embolism (PE), are associated with significant mortality, morbidity, and cost in hospitalized patients. To evaluate the success of preventive measures,...

Quantifying care coordination using natural language processing and domain-specific ontology.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This research identifies specific care coordination activities used by Aging in Place (AIP) nurse care coordinators and home healthcare (HHC) nurses when coordinating care for older community-dwelling adults and suggests a method to quanti...

Evaluating the state of the art in disorder recognition and normalization of the clinical narrative.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The ShARe/CLEF eHealth 2013 Evaluation Lab Task 1 was organized to evaluate the state of the art on the clinical text in (i) disorder mention identification/recognition based on Unified Medical Language System (UMLS) definition (Task 1a) a...

Automated clinical trial eligibility prescreening: increasing the efficiency of patient identification for clinical trials in the emergency department.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: (1) To develop an automated eligibility screening (ES) approach for clinical trials in an urban tertiary care pediatric emergency department (ED); (2) to assess the effectiveness of natural language processing (NLP), information extractio...

The emergence of large language models as tools in literature reviews: a large language model-assisted systematic review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This study aims to summarize the usage of large language models (LLMs) in the process of creating a scientific review by looking at the methodological papers that describe the use of LLMs in review automation and the review papers that me...

Development and validation of the provider documentation summarization quality instrument for large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: As large language models (LLMs) are integrated into electronic health record (EHR) workflows, validated instruments are essential to evaluate their performance before implementation and as models and documentation practices evolve. Existi...

Recovering missing electronic health record mortality data with a machine learning-enhanced data linkage process.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a continual process for linking more comprehensive external mortality data to electronic health records (EHRs) for a large healthcare system, which can serve as a template for other healthcare systems.

Detecting emergencies in patient portal messages using large language models and knowledge graph-based retrieval-augmented generation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This study aims to develop and evaluate an approach using large language models (LLMs) and a knowledge graph to triage patient messages that need emergency care. The goal is to notify patients when their messages indicate an emergency, gu...

Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Large language models (LLMs) have shown potential in biomedical applications, leading to efforts to fine-tune them on domain-specific data. However, the effectiveness of this approach remains unclear. This study aims to critically evaluat...