Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data

Fonseca, André; Spytek, Mikolaj; Biecek, Przemysław; Cordeiro, Clara; Sepúlveda, Nuno

http://hdl.handle.net/10400.1/20396

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
13040_2024_Article_354.pdf		2.72 MB	Adobe PDF	Download

Send Feedback

Authors

Abstract(s)

Nowadays, the chance of discovering the best antibody candidates for predicting clinical malaria has notably increased due to the availability of multi-sera data. The analysis of these data is typically divided into a feature selection phase followed by a predictive one where several models are constructed for predicting the outcome of interest. A key question in the analysis is to determine which antibodies should be included in the predictive stage and whether they should be included in the original or a transformed scale (i.e. binary/dichotomized).