Discovering symptom patterns of COVID-19 patients using association rule mining.
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| Title: | Discovering symptom patterns of COVID-19 patients using association rule mining. |
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| Authors: | Tandan M; Cecil G Sheps Center for Health Service Research, University of North Carolina, Chapel Hill, USA. Electronic address: meerat@email.unc.edu., Acharya Y; Western Vascular Institute, Galway University Hospital, Galway, Ireland. Electronic address: dryogeshach@gmail.com., Pokharel S; The University of Queensland, St Lucia, Queensland, Australia. Electronic address: s.pokharel@uq.edu.au., Timilsina M; Data Science Institute, Insight Centre for Data Analytics, National University of Ireland Galway, Ireland. Electronic address: mohan.timilsina@insight-centre.org. |
| Source: | Computers in biology and medicine [Comput Biol Med] 2021 Apr; Vol. 131, pp. 104249. Date of Electronic Publication: 2021 Feb 01. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1879-0534 |
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| DOI: | 10.1016/j.compbiomed.2021.104249 |
