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

André FonsecaMikolaj SpytekPrzemysław BiecekClara CordeiroNuno Sepúlveda
Published in: BioData mining (2024)
The three feature selection strategies provided a better predictive performance of the outcome when compared to the previous results relying on Random Forest including all the 36 antibodies (AUC = 0.68, 95% CI = [0.57;0.79]). Given the similar predictive performance, we recommended that the three strategies should be used in conjunction in the same data set and selected according to their complexity.
Keyphrases
  • electronic health record
  • big data
  • climate change
  • deep learning
  • artificial intelligence
  • plasmodium falciparum