Juan (Wendy) Zhao, PhD

Research Assistant Professor

ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes

Journal article

Juan Zhao, Monika E. Grabowska, Vern Eric Kerchberger, Joshua C. Smith, H. Nur Eken, QiPing Feng, Josh F. Peterson, S. Trent Rosenbloom, Kevin B. Johnson, Wei-Qi Wei
Journal of Biomedical Informatics, vol. 117, 2021 May, p. 103748
Cite

Cite

APA
Zhao, J., Grabowska, M. E., Kerchberger, V. E., Smith, J. C., Eken, H. N., Feng, Q. P., … Wei, W.-Q. (2021). ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes. Journal of Biomedical Informatics, 117, 103748.

Chicago/Turabian
Zhao, Juan, Monika E. Grabowska, Vern Eric Kerchberger, Joshua C. Smith, H. Nur Eken, QiPing Feng, Josh F. Peterson, S. Trent Rosenbloom, Kevin B. Johnson, and Wei-Qi Wei. “ConceptWAS: A High-Throughput Method for Early Identification of COVID-19 Presenting Symptoms and Characteristics from Clinical Notes.” Journal of Biomedical Informatics 117 (May 2021): 103748.

MLA
Zhao, Juan, et al. “ConceptWAS: A High-Throughput Method for Early Identification of COVID-19 Presenting Symptoms and Characteristics from Clinical Notes.” Journal of Biomedical Informatics, vol. 117, May 2021, p. 103748.

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