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CogStack represents a major advance in the capacity to extract and analyse unstructured data from electronic health records (EHRs). It uses a range of technologies to support modern open-source...
A team of researchers processed and converted over 1.3 billion rows of UK Biobank data to the Observational Medical Outcomes Partnership (OMOP) common data model (CDM), improving its usability for...
Researchers have applied machine learning to improve the detection of heart damage through cardiac magnetic resonance (CMR) scans.
Researched used nationwide patient data to evaluate the effectiveness of the NEWS2 score for predicting who was at greatest risk of intensive care.
People with severe mental illness have a lower life expectancy and a higher risk of physical conditions. To improve how these comorbidities can be detected and predicted, researchers have used...
People with severe mental illness, such as schizophrenia spectrum disorders or bipolar disorders, have higher death rates. It is difficult to study mental health records at scale, so a team of...
Being able to link addresses across systems offers a valuable resource for health data science. However, they are often not standardised despite a government push towards this. Researchers at the...
Overview Alzheimer’s disease (AD) is a highly prevalent form of dementia – the genetic variations underlying the disease are poorly understood and the number and effectiveness of drug...
Overview Researchers have used new artificial intelligence (AI) techniques to identify which patients with heart failure do, or do not, benefit from beta blockers. Their approach interrogates data...