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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.
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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 firstWe describe the harmonisation of five UK electronic birth cohorts to the Observational Medical Outcomes Partnership (OMOP) Common Data Model, creating a large-scale, standardised resource for maternal and child health research. The Mother and Infant Research Data Analysis (MIREDA) partnership developed and implemented reproducible guidelines for mapping maternal-infant relationships and identifying pregnancy episo…
Open article record in new tab ↗Background Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and the presence of restricted or repetitive behaviors. Although its underlying pathophysiological mechanisms remain unclear, growing evidence indicates that neuroinflammation plays a significant role, especially in children. Objective This study aims to explore neuroinflammatory pathways i…
IntroductionApplication of data science in Maternal, Newborn, and Child Health (MNCH) across Africa is variable with limited documentation. Despite efforts to reduce preventable MNCH morbidity and mortality, progress remains slow. Accurate data is crucial for holding countries accountable, tracking progress towards realisation of SDG3 targets on MNCH, and guiding interventions. Data science can improve data availa…
Open article record in new tab ↗BackgroundArtificial intelligence (AI) models applied to diabetes mellitus research have grown in recent years, particularly in the field of medical imaging. However little work has been done exploring real-world data (RWD) sources such as electronic health records (EHR) mostly due to the lack of reliable public diabetes databases. However, with more than 500 million patients affected worldwide, complications of t…
ImportanceAcute Hepatic Porphyria (AHP) is a group of rare but treatable conditions associated with diagnostic delays of fifteen years on average. The advent of electronic health records (EHR) data and machine learning (ML) may improve the timely recognition of rare diseases like AHP. However, prediction models can be difficult to train given the limited case numbers, unstructured EHR data, and selection biases in…
BackgroundApproaches to addressing unwarranted variation in healthcare service delivery have traditionally relied on the prospective identification of activities and outcomes, based on a hypothesis, with subsequent reporting against defined measures. Practice-level prescribing data in England are made publicly available by the NHS Business Services Authority for all general practices. There is an opportunity to ad…
Open article record in new tab ↗Youths experiencing homelessness (YEH) often cycle between various sheltering locations including spending nights on the streets, in shelters and with others. Few studies have explored the patterns of daily sheltering over time. A total of 66 participants completed 724 ecological momentary assessments that assessed daily sleeping arrangements. Analyses applied a hypothesis-generating machine learning algorithm (co…