In order to understand possible barriers and facilitators to the use of an early warning track and trigger system in Kenya, a stakeholder meeting was held in July 2019 in Nairobi. This was attended by ...

Talk about a kid with a lot of heart. A 14-year-old from Frisco, Texas, developed a groundbreaking smartphone app to detect ...

We've tested a range of carbon monoxide alarms—from smart devices with app connectivity to budget-friendly basics—to find the ...

Researchers at ETH Zurich have created a first-of-its-kind wearable device that gives women an easy way to do a health check.

Accordingly, we propose a system and the related methods for detecting CA before the CPR event occurred earlier and it is not only assisting physicians to early diagnose of CA and immediately warning ...

a novel dynamic network construction algorithm for identifying early warning signals based on a data-driven approach (EWS-DDA) was proposed. In EWS-DDA, the shrunken centroid was introduced to measure ...

Objectives The utility of New Zealand Early Warning Score (NZEWS) for prediction of adversity ... variables or it may be a single extreme parameter to trigger a rapid system response.1 2 The patients ...

Our recent evidence-based, theoretically informed, Paediatric early warning system - Utilisation and Mortality Avoidance. improvement programme (PUMA Programme) was developed and implemented in two ...

Background: The modified early warning score (MEWS) is a useful tool for identifying hospitalised patients in need of a higher level of care and those at risk of inhospital death. Use of the MEWS as a ...

New research by Edwards Lifesciences has demonstrated that early intervention for severe aortic stenosis ... Medtronic recently released two-year results from a clinical trial comparing its Evolut ...

Environment Secretary Dr Deborah Barasa leads launch of the latest Early Warning for All Initiative (EA4All) government-led disaster programme in Nairobi yesterday. She was accompanied (left to ...

The research, completed in November 2024, analyzed 2,867 claims from 2020 to 2024 using an unsupervised machine learning approach. Nine percent of open claims were identified as high potential for ...