Fernández-Leal A, Moret-Bonillo V
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:1039-42. doi: 10.1109/IEMBS.2007.4352472.
This article describes the results of the application of a framework for handling temporal information--based on the causal temporal constraint network model--to a sleep apneas syndrome diagnostic system. This approach enables the temporal quantitative, qualitative and causal constraints between events (which can be points (instants) or intervals) to be represented and processed, ensures greater precision in the identification of diagnostic patterns, and introduces a method for handling inexact knowledge in sleep apneas syndrome diagnosis.
本文描述了一种基于因果时间约束网络模型的处理时间信息的框架应用于睡眠呼吸暂停综合征诊断系统的结果。这种方法能够表示和处理事件（可以是时间点（瞬间）或时间段）之间的时间定量、定性和因果约束，确保在识别诊断模式时具有更高的精度，并引入了一种在睡眠呼吸暂停综合征诊断中处理不精确知识的方法。
