BACKGROUND: Manual review of electronic health records for clinical research is labor-intensive and prone to reviewer-dependent variations. Large language models (LLMs) offer potential for automated clinical data extraction; however, their feasibilit...
Named Entity Recognition (NER) plays a crucial role in extracting important information such as treatment methods, symptoms, and herbal prescriptions from Traditional Chinese Medicine (TCM) electronic medical records. However, existing NER methods of...
BACKGROUND: Inflammatory bowel disease (IBD) research is a dynamic field. However, the growing volume of electronic health records (EHRs) and research data presents significant challenges. Traditional methods for structuring unstructured EHRs are lab...
BMC medical informatics and decision making
Oct 31, 2025
BACKGROUND: Labor- and cost-intensive manual chart review of Electronic Health Records (EHRs) remains a major bottleneck in retrospective studies, particularly when rare-disease cohorts require high specificity. Automated Natural Language Processing ...
PURPOSE: Objectives were to develop a machine learning (ML) model based on electronic health record (EHR) data to predict the risk of vomiting within a 96-hour window after admission to the pediatric oncology and hematopoietic cell transplant (HCT) s...
BMC medical informatics and decision making
Oct 29, 2025
BACKGROUND: In clinical research, there is a strong drive to leverage big data from population cohort studies and routine electronic healthcare records to design new interventions, improve health outcomes and increase the efficiency of healthcare del...
Cardiovascular disease (CVD) is considered the number one killer disease in the world, underlining the importance of the application of more accurate diagnostic and therapeutic tools. Traditional screening procedures usually do not provide identifica...
BACKGROUND/AIMS: To investigate the landscape to support Europe-wide collaborative real-world data (RWD) collection, exploring whether required resources are available to glaucoma clinicians.
BACKGROUND: Metabolic dysfunction associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide and affects >25% in the United States population. We hypothesized that clinical features present in electronic health r...
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