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Observational Studies as Topic

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Utilising causal inference methods to estimate effects and strategise interventions in observational health data.

PloS one
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...

Machine learning of blood haemoglobin and haematocrit levels via smartphone conjunctiva photography in Kenyan pregnant women: a clinical study protocol.

BMJ open
INTRODUCTION: Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk to both maternal and neonatal health. The primary challenge is that anaemia is frequently undetected ...

Machine learning for outcome prediction in patients with non-valvular atrial fibrillation from the GLORIA-AF registry.

Scientific reports
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...

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
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
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 ...

Multicategory matched learning for estimating optimal individualized treatment rules in observational studies with application to a hepatocellular carcinoma study.

Statistical methods in medical research
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...

AI-DBS study: protocol for a longitudinal prospective observational cohort study of patients with Parkinson's disease for the development of neuronal fingerprints using artificial intelligence.

BMJ open
INTRODUCTION: Deep brain stimulation (DBS) is a proven effective treatment for Parkinson's disease (PD). However, titrating DBS stimulation parameters is a labourious process and requires frequent hospital visits. Additionally, its current applicatio...