Found total of 7 items
CORONET Nominated for NIHR Clinical Excellence Award
A tool created in conjunction with the Digital Experimental Cancer Medicine Team to support decisions regarding hospital admissions or discharge in cancer patients presenting with symptoms of COVID-19 has been selected for a NIHR Clinical Research Network award.
CHaPEL: Cleanliness is next to...?
Our Mobile Development Service (MDS) has been working with School of Health Sciences PhD student Sewon Lee to assist in building an app on a very limited budget that allows hospital cleaning staff to log exposure to, and usage of, hazardous products in their role.
Helping to Celebrate 200 years of The Guardian Newspaper
University libraries are increasingly hosting their collections online to reach a wider audience, however conventional web publishing platforms, such as WordPress, have been found to lack essential features that are required in digital collections. This is where dedicated digital collections platforms step in to provide the specialist set of technologies that would otherwise not be available.
CORONET COVID-19 Risk in Oncology Evaluation Tool - Phase II
In January 2021, our Research Software Engineers worked with the Digital Experimental Cancer Medicine Team (dECMT) to create a tool to support decisions regarding hospital admissions or discharge in cancer patients presenting with symptoms of COVID-19. The tool has been so successful that multiple improvements are now planned.
Village Stories Launch
“Missing the Village? We all do. Researchers at University of Manchester are looking to hear about your experiences of the Manchester Village and what you want it to be in the future. You can share them anonymously on the new Manchester Village Stories website and make your views heard about the Village. #MCRVillageStories. ”
CORONET COVID-19 Risk in Oncology Evaluation Tool Launched
Cancer patients are at increased risk of severe COVID-19. Decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical. The objective of this project was to identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool - COVID-19 Risk in Oncology Evaluation Tool (CORONET).