Prediction of response to antiretroviral therapy by human experts and by the EuResist data‐driven expert system (the EVE study)

By Maurizio Zazzi, R. Kaiser, Anders Sönnerborg, Daniel Struck, André Altmann, Mattia C. F. Prosperi, M. Rosen-Zvi, A. Petróczi, Y. Peres, Eugen Schülter and 14 more. 2010

54 citations recorded by the source corpus.

The EuResist expert system is a novel data‐driven online system for computing the probability of 8‐week success for any given pair of HIV‐1 genotype and combination antiretroviral therapy regimen plus optional patient information. The objective of this study was to compare the EuResist system vs. human experts (EVE) for the ability to predict response to treatment.

Subfields: Infectious Diseases, Virology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Infectious Diseases

1. Maurizio Zazzi
2. Vukosi Marivate

In Virology

1. Maurizio Zazzi
2. Vukosi Marivate

Citations in the corpus

• Predicting Response to Antiretroviral Treatment by Machine Learning: The EuResist Project (2012, background): “One out of the ten experts failed only 6 predictions as the EuResist system had, while all the others failed larger numbers of predictions [15] .”