2024 · Computers in biology and medicine · paywalled
Adaptive convolutional dictionary learning for denoising seismocardiogram to enhance the classification performance of aortic stenosis
Xu et al.
The finding, in our words
An adaptive convolutional dictionary learning method denoised wearable seismocardiogram recordings from 50 subjects, improving aortic stenosis classification accuracy by 13.8 per cent to reach 90.2 per cent. This enhancement of signal quality addresses instrumentation constraints that limit remote cardiac monitoring.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
A direct-to-participant, multichannel recruitment strategy enrolled 34,244 older adults into a virtual trial testing an Apple Watch based heart health programme with electrocardiogram and irregular rhythm notification features, achieving broad geographic and gender diversity but under-representing non-White ethnic groups.
Analysis of six studies revealed that decentralised clinical trial elements enhanced data completeness by enabling direct access to medical records, although this introduced a significant burden for data abstraction. The results suggest that decentralised approaches are not a universal solution but provide specific metrics that can help design fit-for-purpose trials.
Wearable-derived digital biomarkers have been accepted by regulatory agencies as endpoints in clinical trials for Duchenne muscular dystrophy, showing their potential to support decentralised diagnostics through patient-centric monitoring. This matters because it enables more sensitive and continuous assessment of disease progression outside clinical settings.
Ma et al., Neurology and therapy (paywalled) · source ↗
The High-Definition Oncology feasibility study in 30 women with metastatic cancer demonstrated high adherence to biospecimen collection (97.4% plasma, 80.7% stool) and wearable monitoring (70–95% of days captured for activity, heart rate, sleep, and oxygen saturation). This establishes a viable framework for decentralised, multimodal data collection in oncology to support individualised treatment models.
Garma et al., JCO precision oncology (paywalled) · source ↗
A 2025 review from China finds decentralised trials still far from standard practice despite the enthusiasm of regulators and industry, and names the operational gaps that keep them so: technology, oversight and data quality.