BMC medical informatics and decision making
Oct 22, 2025
BACKGROUND: Carbapenemase-Producing Enterobacteriace (CPE) poses a critical concern for infection prevention and control in hospitals. However, predictive modeling of previously highlighted CPE-associated risks such as readmission, mortality, and ext...
BACKGROUND: It remains unclear whether certain individuals with type 2 diabetes (T2D) derive greater cardiovascular benefit from GLP-1 receptor agonists (GLP-1RAs). Here, we integrate individual-level data from cardiovascular outcome trials (CVOTs) a...
BACKGROUND: Machine learning (ML) models have shown good performance in predicting cardiovascular disease risk. However, the usefulness of ML models has yet to be fully elucidated for sudden cardiac death (SCD) risk using long-term follow-up electron...
Depression in seniors is a growing public health concern worldwide. Despite the rising prevalence of depression in this demographic, comprehensive data on its burden and trends over an extended period remain limited. This study aims to assess the tre...
BACKGROUND: Hypertension affects 31% of the global adult population. Artificial intelligence-based chatbots may support self-management of hypertension and other chronic disorders. Chronic Disease Management Program (CHAMP) is a digital health interv...
BACKGROUND: Clinical natural language processing (cNLP) techniques are commonly developed and used to extract information from clinical notes to facilitate clinical decision-making and research. However, they are less established for rare diseases su...
This study presents a machine learning-driven model predicting all-cause mortality two years in advance using administrative health data focused on diabetic patients. Integrating hospitalization records, emergency department data, demographics, and c...
BACKGROUND: Chronic obstructive pulmonary disease (COPD) remains a leading global health burden. In primary care, the inconsistent availability of spirometry and symptom scores limits the detection of patients with poor disease control. There is a pr...
OBJECTIVE: Natural language processing (NLP) can identify cohorts of patients with inflammatory bowel disease (IBD) from free text. However, limited sharing of code, models, and data sets continues to hinder progress. The aim of this study was to eva...
BMC medical informatics and decision making
Oct 7, 2025
BACKGROUND: Well-organised electronic health records (EHR) are essential for high quality patient care, but EHR user interfaces can be cumbersome for entry of structured information, resulting in the majority of information being in free text rather ...
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