Leveraging artificial intelligence and data science techniques in harmonizing, sharing, accessing and analyzing SARS-COV-2/COVID-19 data in Rwanda (LAISDAR Project): study design and rationale

Article, BMC Medical Informatics and Decision Making, 22-Aug-2022

Aurore Nishimwe¹, Charles Ruranga², Clarisse Musanabaganwa³, Regine Mugeni⁴, Muhammed Semakula³, Joseph Nzabanita⁵, Ignace Kabano², Annie Uwimana², Jean N. Utumatwishima⁴, Jean Damascene Kabakambira⁶, Annette Uwineza⁶, Lars Halvorsen⁷, Freija Descamps⁷, Jared Houghtaling⁷, Benjamin Burke⁷, Odile Bahati⁸, Clement Bizimana⁸, Stefan Jansen¹, Celestin Twizere⁹, Kizito Nkurikiyeyezu⁹, Francine Birungi¹, Sabin Nsanzimana³ and Marc Twagirumukiza¹,¹⁰
[1] College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda. [2] African Center of Excellence in Data Science, University of Rwanda, Kigali, Rwanda. [3] Rwanda Biomedical Center, Ministry of Health, Kigali, Rwanda. [4] Rwamagana Provincial Hospital, East province, Rwamagana, Rwanda. [5] College of Science and Technology, University of Rwanda, Kigali, Rwanda. [6] The University Teaching Hospital of Kigali (CHUK), Kigali, Rwanda. [7] edenceHealth NV, Kontich, Belgium. [8] Regional Alliance of Sustainable Development, Kigali, Rwanda. [9] Center of Excellence in Biomedical Engineering and eHealth, University of Rwanda, Kigali, Rwanda. [10] Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium