Temporal knowledge in the intelligent diagnosis of sleep apnea syndrome: a new approach.
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.
Fernández-Leal
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Moret-Bonillo
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D000465:Algorithms; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D017286:Polysomnography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012891:Sleep Apnea Syndromes / Q000175:diagnosis*; D012984:Software; D013997:Time Factors