Assessment of temporal predictive models for health care using a formal method

Recent developments in the field of sensor devices provide new possibilities to measure a variety of health related aspects in a precise and fine-grained manner. Subsequently, more empirical data will be generated than ever before. While this greatly improves the opportunities for creating accurate predictive models, other types of models besides the more traditional machine learning approaches can provide insights into temporal relationships in the data. Models that express temporal relationships between states in a mathematical manner are examples of such models.

Source: Computers in Biology and Medicine - June 17, 2017 Category: Bioinformatics Authors: Ward van Breda, Mark Hoogendoorn, A.E. Eiben, Matthias Berking Source Type: research