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

BACKGROUND: Since the outbreak of COVID-19 pandemic in Rwanda, a vast amount of SARS-COV-2/COVID-19-related data have been collected including COVID-19 testing and hospital routine care data. Unfortunately, those data are fragmented in silos with different data structures or formats and cannot be us...

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Detalles Bibliográficos
Autores principales: Nishimwe, Aurore, Ruranga, Charles, Musanabaganwa, Clarisse, Mugeni, Regine, Semakula, Muhammed, Nzabanita, Joseph, Kabano, Ignace, Uwimana, Annie, Utumatwishima, Jean N., Kabakambira, Jean Damascene, Uwineza, Annette, Halvorsen, Lars, Descamps, Freija, Houghtaling, Jared, Burke, Benjamin, Bahati, Odile, Bizimana, Clement, Jansen, Stefan, Twizere, Celestin, Nkurikiyeyezu, Kizito, Birungi, Francine, Nsanzimana, Sabin, Twagirumukiza, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372951/
https://www.ncbi.nlm.nih.gov/pubmed/35962355
http://dx.doi.org/10.1186/s12911-022-01965-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372951/
https://www.ncbi.nlm.nih.gov/pubmed/35962355
http://dx.doi.org/10.1186/s12911-022-01965-9

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