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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
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 |
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