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Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
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Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
7 articles
Newest firstDeep learning models utilizing longitudinal healthcare data have significantly advanced epidemiological research. However, contemporary transformer-based models increasingly rely on computationally intensive pre-training steps that entail processing massive real-world datasets with cost-prohibitive hardware. We introduce the Temporal Encoder with Late Fusion (TELF), a lightweight end-to-end predictive model featur…
Open article record in new tab ↗Cardiovascular diseases (CVDs) present multifactorial pathophysiology and produce immense health and economic burdens globally. The most common type, coronary artery disease (CAD), shows a complex etiology with multiple genetic variants to interplay with various clinical features and demographic traits affecting CAD risk and severity. The development and clinical validation of machine learning (ML) algorithms that…
ObjectivesPrevention of fetal growth restriction/small for gestational age is adequate if screening is accurate. Ultrasound and biomarkers can achieve this goal; however, both are often inaccessible. This study aimed to develop, validate, and deploy a prognostic prediction model for screening fetal growth restriction/small for gestational age using only medical history. MethodsFrom a nationwide health insurance da…
Stones in the common bile duct (CBD) are reported worldwide, and this condition is majorly managed through endoscopic retrograde cholangiopancreatography (ERCP). CBD stone recurrence is an important issue after endoscopic stone removal. Therefore, it is essential to identify its risk factors to determine the necessity of regular follow-up in patients who underwent endoscopic removal of CBD stones. The authors iden…
Open article record in new tab ↗ImportancePrognostic predictions of prelabor rupture of membranes lack proper sample sizes and external validation. ObjectiveTo develop, validate, and deploy statistical and/or machine learning prediction models using medical histories for prelabor rupture of membranes and the time of delivery. DesignA retrospective cohort design within 2-year period (2015 to 2016) of a single-payer, government-owned health insura…
Open article record in new tab ↗BackgroundDigital systems have long been used to improve the quality and safety of care when managing Acute Kidney Injury (AKI). The availability of digitised clinical data can also turn organisations and their networks into Learning Healthcare Systems (LHSs) if used across all levels of health and care. This review explores the impact of digital systems on AKI patient care to gauge progress towards establishing L…
Open article record in new tab ↗BACKGROUND: Risk prediction algorithms have long been used in health research and practice (e.g. prediction of cardiovascular disease and diabetes). However, similar tools have not been developed for mental health. For example, for psychotic disorders, attempts to sum environmental risk are rare, unsystematic and dictated by available data. In light of this, we sought to develop a valid, easy to use measure of the…
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