Philips Foundation Connects KIU to the Global Efforts against COVID-19 with FAIR
Posted by rohny01 on March 20th, 2020
Following the COVID-19 outbreak, Kampala International University has joined the Virus Outbreak Data Network (VODAN) GO FAIR Implementation Network, which addresses current and immediate challenges to use and connect digital health data worldwide to combat the COVID-19 pandemic. This initiative is to ensure that universities on the African continent are connected to the global effort to fight COVID-19 and to ensure Africa’s health professional and data scientists are equipped to harness machine-learning and artificial intelligence (AI) approaches, to discover meaningful patterns in epidemic outbreaks. The data will be FAIR (Findable, Accessible, Interoperable, and Resuable).
VODAN ensures that medical data are discoverable by computers and accessible under governance regulations. The African patient data remain under the regulations of ministries of health. These data will not be displaced as they’re visited by the algorithms based on the access accorded to the data by the data stewards. The findability of quality data will empower AI solutions that will help end the crisis. The infrastructure will remain in place after the crisis, to strengthen health systems and to respond to future outbreaks.
Kampala International University entered in a partnership with Philips Foundation whose mission is to provide access to care for undeserved communities and the GO FAIR Foundation to set up the training. The capacity training is led by the GO FAIR Foundation. Any computer science/data science and medical/health science university can join the initiative. KIU has partnered with Leiden University to support joint research based on the data that are available for analysis under this programme
KIU Visiting Professor from University of Leiden, Mirjam van Reisen leads the initiative which is coordinated by Professor Francisca Oladipo. PhD student University of Leiden, Mariam Basajja, is leading the technical team.
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