Author: Pawel Dlotko; Simon Rudkin
Title: Covid-19 clinical data analysis using Ball Mapper Document date: 2020_4_15
ID: a5fdeuvv_33
Snippet: The copyright holder for this preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Figure 3 is obtained. As one can observe, Ball number 1 contains a lot of such patients, but also ball number 16 and 25 is clearly visible and majority of patients over there wil require ICU. In our next exercise we will focus on the patients whic.....
Document: The copyright holder for this preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Figure 3 is obtained. As one can observe, Ball number 1 contains a lot of such patients, but also ball number 16 and 25 is clearly visible and majority of patients over there wil require ICU. In our next exercise we will focus on the patients which have positive values of tests for SARS-Cov2. To obtain them the following code is used: Let us observe which of those patients end up in normal ward, semi intensive and intensive care. For that purpose the following code is used. Once again, the value = 5 is chosen to optimise the information tractability trade off.
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