Conference paper Open Access
López, Beatriz; Viñas, Ramon; Torrent-Fontbona, Ferran; Fernández-Real, José Manuel
Machine learning techniques are the cornerstone to handle the amounts of information available for building comprehensive models for decision support in medical practice. However, the datasets use to have a lot of missing information. In this work we analyse how the random forests technique could be used for dealing with missing phenotype values in order to prognosticate diabetes type 2.