Data-driven test strategy for COVID-19 using machine learning: A study in Lahore, Pakistan.

ABSTRACT:

Aims

We aimed at giving a preliminary analysis of the weakness of a current test strategy, and proposing a data-driven strategy that was self-adaptive to the dynamic change of pandemic. The effect of driven-data selection over time and space was also within the deep concern.

Methods

A mathematical definition of the test strategy were given. With the real COVID-19 test data from March to July collected in Lahore, a significance analysis of the possible features was conducted. A machine learning method based on logistic regression and priority ranking were proposed for the data-driven test strategy. With performance assessed by the area under the receiver operating characteristic curve (AUC), time series analysis and spatial cross-test were conducted.

Results

The transi

SUBMITTER: Huang C 

PROVIDER: S-EPMC8184360 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature