Using Machine Learning Techniques and National Tuberculosis Surveillance Data to Predict Excess Growth in Genotyped Tuberculosis Clusters

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作者： Althomsons, Sandy P. ^[1] ; Winglee, Kathryn ^[2] ; Heilig, Charles M. ; Talarico, Sarah ; Silk, Benjamin ; Wortham, Jonathan ; Hill, Andrew N. ; Navin, Thomas R.

作者单位： Ctr Surveillance Epidemiol & Lab Serv,Ctr Dis Control & Prevent ^[1] Centers for Disease Control & Prevention - USA,CDC ^[2]

关键词 cluster growth machine learning surveillance data tuberculosis RECENT TRANSMISSION UNITED-STATES OUTBREAKS PEOPLE

发布时间 2023-02-15

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American Journal of Epidemiology

2022年191卷11期

1936-1943页

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Using Machine Learning Techniques and National Tuberculosis Surveillance Data to Predict Excess Growth in Genotyped Tuberculosis Clusters

American Journal of Epidemiology

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American Journal of Epidemiology

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Using Machine Learning Techniques and National Tuberculosis Surveillance Data to Predict Excess Growth in Genotyped Tuberculosis Clusters

American Journal of Epidemiology

相似文献

American Journal of Epidemiology

相关期刊

检索历史清除