Who was at risk for COVID-19 late in the US pandemic? Insights from a population health machine learning model.
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| Title: | Who was at risk for COVID-19 late in the US pandemic? Insights from a population health machine learning model. |
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| Authors: | Adeoye EA; Providence St. Joseph Health, 1801 Lind Avenue S.W. Valley Office Park, Morin Bldg, 1st Floor, Renton, WA, 98057-9016, USA., Rozenfeld Y; Providence St. Joseph Health, 1801 Lind Avenue S.W. Valley Office Park, Morin Bldg, 1st Floor, Renton, WA, 98057-9016, USA. Yelena.Rozenfeld@providence.org., Beam J; Providence St. Joseph Health, 1801 Lind Avenue S.W. Valley Office Park, Morin Bldg, 1st Floor, Renton, WA, 98057-9016, USA., Boudreau K; Providence St. Joseph Health, 1801 Lind Avenue S.W. Valley Office Park, Morin Bldg, 1st Floor, Renton, WA, 98057-9016, USA., Cox EJ; Providence Medical Research Center, 105 W 8th Ave, Suite 250E, Spokane, WA, 99204, USA., Scanlan JM; Swedish Center for Research and Innovation, 800 Fifth Ave, 11th floor, Seattle, WA, USA. |
| Source: | Medical & biological engineering & computing [Med Biol Eng Comput] 2022 Jul; Vol. 60 (7), pp. 2039-2049. Date of Electronic Publication: 2022 May 11. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: United States NLM ID: 7704869 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1741-0444 (Electronic) Linking ISSN: 01400118 NLM ISO Abbreviation: Med Biol Eng Comput Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1741-0444 |
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| DOI: | 10.1007/s11517-022-02549-5 |
