AIMC Topic: Observational Studies as Topic
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Jackalope Plus tool for post-coordination, ontology development, and precise mapping in observational health studies.
Scientific reports
Jul 2, 2025
Accurate mapping of complex health data to the OMOP CDM while preserving clinical nuance remains a challenge. We introduce Jackalope Plus, a novel tool leveraging SNOMED CT post-coordination and a GPT-4o mini LLM, to significantly enhance the precisi...
Characterising physical activity patterns in community-dwelling older adults using digital phenotyping: a 2-week observational study protocol.
BMJ open
May 24, 2025
INTRODUCTION: Physical activity (PA) is crucial for older adults' well-being and mitigating health risks. Encouraging active lifestyles requires a deeper understanding of the factors influencing PA, which conventional approaches often overlook by ass...
Multicategory matched learning for estimating optimal individualized treatment rules in observational studies with application to a hepatocellular carcinoma study.
Statistical methods in medical research
Jan 23, 2025
One primary goal of precision medicine is to estimate the individualized treatment rules that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in practice. However, most...
Clinical validation of an artificial intelligence-based decision support system for diagnosis and risk stratification of heart failure (STRATIFYHF): a protocol for a prospective, multicentre longitudinal study.
BMJ open
Jan 7, 2025
INTRODUCTION: Heart failure (HF) is a complex clinical syndrome. Accurate risk stratification and early diagnosis of HF are challenging as its signs and symptoms are non-specific. We propose to address this global challenge by developing the STRATIFY...
Utilising causal inference methods to estimate effects and strategise interventions in observational health data.
PloS one
Dec 30, 2024
Randomised controlled trials (RCTs) are the gold standard for evaluating health interventions but often face ethical and practical challenges. When RCTs are not feasible, large observational data sets emerge as a pivotal resource, though these data s...
StUdy of Gestational diabetes And Risk using Electronic Data (SUGARED): a population-based cohort study-study protocol.
BMJ open
Dec 26, 2024
INTRODUCTION: The incidence of gestational diabetes mellitus (GDM) in Australia has tripled in the last 20 years. Consequently, over 40 000 pregnancies are now diagnosed as 'higher risk' each year. This has increased antenatal surveillance and obstet...
Humans
Research Design
Retrospective Studies
New South Wales
Risk Assessment
Pregnancy
Information Storage and Retrieval
Logistic Models
Hospitals, Public
Incidence
Female
Observational Studies as Topic
Propensity Score
Routinely Collected Health Data
Pregnancy Outcome
Diabetes, Gestational
Delivery, Obstetric
Predictive Learning Models
Glucose Tolerance Test
Multilevel Analysis
Employing artificial intelligence for optimising antibiotic dosages in sepsis on intensive care unit: a study protocol for a prospective observational study (KI.SEP).
BMJ open
Dec 12, 2024
INTRODUCTION: In sepsis treatment, achieving and maintaining effective antibiotic therapy is crucial. However, optimal antibiotic dosing faces challenges due to significant variability among patients with sepsis. Therapeutic drug monitoring (TDM), th...
Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO).
BMJ open
Dec 2, 2024
PURPOSE: Coronary CT angiography (CCTA) is well established for the diagnostic evaluation and prognostication of coronary artery disease (CAD). The growing burden of CAD in Asia and the emergence of novel CT-based risk markers highlight the need for ...
Machine learning for outcome prediction in patients with non-valvular atrial fibrillation from the GLORIA-AF registry.
Scientific reports
Nov 7, 2024
Clinical risk scores that predict outcomes in patients with atrial fibrillation (AF) have modest predictive value. Machine learning (ML) may achieve greater results when predicting adverse outcomes in patients with recently diagnosed AF. Several ML m...
Mobil Monitoring Doppler Ultrasound (MoMDUS) study: protocol for a prospective, observational study investigating the use of artificial intelligence and low-cost Doppler ultrasound for the automated quantification of hypertension, pre-eclampsia and fetal growth restriction in rural Guatemala.
BMJ open
Sep 10, 2024
INTRODUCTION: Undetected high-risk conditions in pregnancy are a leading cause of perinatal mortality in low-income and middle-income countries. A key contributor to adverse perinatal outcomes in these settings is limited access to high-quality scree...
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