A machine learning PROGRAM to identify COVID-19 and other diseases from hematology data

AIM: We propose a method for screening full blood count metadata for evidence of communicable and noncommunicable diseases using machine learning (ML). MATERIALS & METHODS: High dimensional hematology metadata was extracted over an 11-month period from Sysmex hematology analyzers from 43,761 pat...

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Detalles Bibliográficos
Autores principales: Gladding, Patrick A, Ayar, Zina, Smith, Kevin, Patel, Prashant, Pearce, Julia, Puwakdandawa, Shalini, Tarrant, Dianne, Atkinson, Jon, McChlery, Elizabeth, Hanna, Merit, Gow, Nick, Bhally, Hasan, Read, Kerry, Jayathissa, Prageeth, Wallace, Jonathan, Norton, Sam, Kasabov, Nick, Calude, Cristian S, Steel, Deborah, Mckenzie, Colin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Science Ltd 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204819/
https://www.ncbi.nlm.nih.gov/pubmed/34254032
http://dx.doi.org/10.2144/fsoa-2020-0207

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204819/
https://www.ncbi.nlm.nih.gov/pubmed/34254032
http://dx.doi.org/10.2144/fsoa-2020-0207

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