Learning temporal rules to forecast instability in continuously monitored patients.
Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may [...]
Author(s): Guillame-Bert, Mathieu, Dubrawski, Artur, Wang, Donghan, Hravnak, Marilyn, Clermont, Gilles, Pinsky, Michael R
DOI: 10.1093/jamia/ocw048