Application of a machine learning algorithm for detection of atrial fibrillation in secondary care.

Atrial fibrillation (AF) is the most common sustained heart arrhythmia and significantly increases risk of stroke. Opportunistic AF testing in high-risk patients typically requires frequent electrocardiogram tests to capture the arrhythmia. Risk-prediction algorithms may help to more accurately identify people with undiagnosed AF and machine learning (ML) may aid in the diagnosis of AF.

Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study.

Aims: To evaluate the ability of a machine learning algorithm to identify patients at high risk of atrial fibrillation in primary care.

Methods: A retrospective cohort study was undertaken using the DISCOVER registry to validate an algorithm developed using a Clinical Practice Research Datalink (CPRD) dataset. The validation dataset included primary care patients in London, England aged ≥30 years from 1 January 2006 to 31 December 2013, without a diagnosis of atrial fibrillation in the prior 5 years.

Neurocognitive training for children with and without AD/HD.

There is accumulating evidence that computerised cognitive training of inhibitory control and/or working memory can lead to behavioural improvement in children with AD/HD. Using a randomised waitlist control design, the present study examined the effects of combined working memory and inhibitory control training, with and without passive attention monitoring via EEG, for children with and without AD/HD. One hundred and twenty-eight children (60 children with AD/HD, 68 without AD/HD) were randomly allocated to one of three training conditions (waitlist; working memory and inhibitory control with attention monitoring; working memory and inhibitory control without attention monitoring) and completed with pre- and post-training assessments of overt behaviour (from 2 sources), trained and untrained cognitive task performance, and resting EEG activity.