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

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Title: A machine learning PROGRAM to identify COVID-19 and other diseases from hematology data.
Authors: Gladding PA; Department of Cardiology, Waitematā District Health Board, Auckland, New Zealand., Ayar Z; Clinical Information Services, Waitematā District Health Board, Auckland, New Zealand., Smith K; Clinical laboratory, Waitematā District Health Board, Auckland, New Zealand., Patel P; Clinical laboratory, Waitematā District Health Board, Auckland, New Zealand., Pearce J; Clinical laboratory, Waitematā District Health Board, Auckland, New Zealand., Puwakdandawa S; Clinical laboratory, Waitematā District Health Board, Auckland, New Zealand., Tarrant D; Clinical laboratory, Waitematā District Health Board, Auckland, New Zealand., Atkinson J; Clinical laboratory, Waitematā District Health Board, Auckland, New Zealand., McChlery E; Clinical laboratory, Waitematā District Health Board, Auckland, New Zealand., Hanna M; Department of Hematology, Waitematā District Health Board, Auckland, New Zealand., Gow N; Department of Infectious diseases, Waitematā District Health Board, Auckland, New Zealand., Bhally H; Department of Infectious diseases, Waitematā District Health Board, Auckland, New Zealand., Read K; Department of Infectious diseases, Waitematā District Health Board, Auckland, New Zealand., Jayathissa P; Institute for Innovation & Improvement (i3), Waitematā District Health Board, Auckland, New Zealand., Wallace J; Institute for Innovation & Improvement (i3), Waitematā District Health Board, Auckland, New Zealand., Norton S; Nanix Ltd, Dunedin, New Zealand., Kasabov N; Knowledge Engineering & Discovery Research Institute (KEDRI), Auckland University of Technology, Auckland, New Zealand., Calude CS; School of Computer Science, University of Auckland, Auckland, New Zealand., Steel D; Sysmex New Zealand Ltd, Auckland, New Zealand., Mckenzie C; Sysmex New Zealand Ltd, Auckland, New Zealand.
Source: Future science OA [Future Sci OA] 2021 Jun 12; Vol. 7 (7), pp. FSO733. Date of Electronic Publication: 2021 Jun 12 (Print Publication: 2021).
Publication Type: Journal Article
Journal Info: Publisher: Taylor & Francis Country of Publication: England NLM ID: 101665030 Publication Model: eCollection Cited Medium: Print ISSN: 2056-5623 (Print) Linking ISSN: 20565623 NLM ISO Abbreviation: Future Sci OA Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2056-5623
DOI:10.2144/fsoa-2020-0207