EZINE:
In this week's Computer Weekly, we find out how computer scientists are using data, cloud and virtual reality to understand the brain and improve mental wellbeing. We analyse newly published government documents detailing the early problems with Universal Credit. And we look at how AI can help improve cyber security. Read the issue now.
EZINE:
In this week's Computer Weekly, we find out how new technologies are supporting the rise of vertical farming, and could revolutionise food supply chains. We examine one of the biggest trends in the cloud – serverless computing. And Brexit has not yet ended the debate about UK-EU data protection. Read the issue now.
WHITE PAPER:
SAS technology has been proven to be the most versatile storage solution in data transfer and high performance. Read this white paper to learn about a solution that renders the necessary performance needed for your client's expanding market requirements.
WHITE PAPER:
This study of over 150 Fortune 1000 firms from every major industry or vertical explores issues associated with the lifeblood of today’s enterprises: data. The findings demonstrate the often dramatic impacts that even marginal investments in information technology can have when that technology addresses data quality, usability, and intelligence.
CASE STUDY:
An integrated delivery network (IDN) faced a challenge: delays in heart failure medical therapy were creating more ED visits and hospitalizations. The solution? The IDN worked with Validic to implement remote care protocols alongside traditional steps, with 66% of patients improving their ejection fraction. Download this case study to learn more.
EGUIDE:
DirectTrust is looking to improve the usability of the Direct standard for use cases such as closed-loop referrals and ADT notifications to drive health data interoperability.
EGUIDE:
Providers must be prepared to address patient needs across the care continuum and be equipped with proper capabilities before joining or establishing an accountable care organization.
WHITE PAPER:
This meta-analysis tracks results across eight studies covering more than 34,711 patients, 19,136 of whom were monitored using the LEAF◊ Patient Monitoring System.
EGUIDE:
Researchers have developed a machine learning (ML) tool capable of using electrocardiogram (ECG) readings to detect and classify heart attacks more quickly and accurately than standard approaches. The model was able to accurately reclassify 1 in 3 patients with chest pain based on heart attack risk. Download the article to read more.
