End-of-life network infrastructure at Dartford and Gravesham NHS Trust (DGT) is putting the ability to use clinical digital systems at risk, according to a board report.
A risk register in trust board paper, published on…
Surgical planning can be highly complicated and personalized, where a surgeon needs to balance multiple decisional dimensions including surgical effectiveness, risk, cost, and patient’s conditions and preferences. Turning to artificial intelligence is a great…
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Deep learning (DL) holds great promise to improve medical diagnostics, including pathology. Current DL research mainly focuses on performance. DL implementation potentially leads to environmental consequences but approaches for assessment of both performance and…
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Background: Effective management of non-communicable diseases requires ongoing coordination and monitoring, often facilitated by e-health technologies such as mobile health (mHealth) applications. The end-user Mobile Application Rating Scale (uMARS) is a valuable tool for…
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Parkinson’s disease (PD) exhibits significant clinical heterogeneity, presenting challenges in the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning techniques have been integrated with resting-state EEG for PD diagnosis, but their practicality is constrained…
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Background: Pregnancy is a pivotal phase in a woman’s life, demanding special attention to ensure maternal and fetal health. Prenatal education plays a vital role in promoting healthy pregnancies and reducing adverse outcomes for…
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Background: Many smartphone apps designed to assist individuals in managing their weight are accessible, but the assessment of app quality and features has predominantly taken place in Western countries. Nevertheless, there is a scarcity…
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The following is a guest article by Doug Bierbower, Vice President of Solutions Engineering at SOLiD Americas
When delivering first-rate care, every aspect of the patient experience is critical. And in today’s always-connected 5G world,…
