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Methods for detecting probable COVID-19 cases from large-scale survey data also reveal probable sex differences in symptom profiles.

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Title: Methods for detecting probable COVID-19 cases from large-scale survey data also reveal probable sex differences in symptom profiles.
Authors: Klein A; Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States., Puldon K; Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, United States., Dilchert S; Department of Management, Zicklin School of Business, Baruch College, The City University of New York, New York, NY, United States., Hartogensis W; Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, United States., Chowdhary A; Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, United States., Anglo C; Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, United States., Pandya LS; Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, United States., Hecht FM; Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, United States., Mason AE; Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, United States., Smarr BL; Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States.; Halicioglu Data Science Institute, University of California, San Diego, La Jolla, CA, United States.
Source: Frontiers in big data [Front Big Data] 2022 Nov 10; Vol. 5, pp. 1043704. Date of Electronic Publication: 2022 Nov 10 (Print Publication: 2022).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media Country of Publication: Switzerland NLM ID: 101770603 Publication Model: eCollection Cited Medium: Internet ISSN: 2624-909X (Electronic) Linking ISSN: 2624909X NLM ISO Abbreviation: Front Big Data Subsets: PubMed not MEDLINE
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