Artificial Intelligence
KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
Readings in qualitative reasoning about physical systems
Readings in qualitative reasoning about physical systems
Generate, test and debug: combining associational rules and causal models
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Model-based interpretation of cardiac beats by evolutionary algorithms: signal and model interaction
Artificial Intelligence in Medicine
On the co-operation between abductive and temporal reasoning in medical diagnosis
Artificial Intelligence in Medicine
A model-based approach to the diagnosis of the cardiac arrhythmias
Artificial Intelligence in Medicine
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A qualitative model of the electrical conducting system of the heart is developed which attempts to represent basic physiological and pathophysiological processes. The state descriptions and state transition rules are used to generate a tree of possible behaviours from a given start state. We demonstrate that without any further knowledge, explosive combinatorial branching occurs, but that information on state durations (expressed either quantitatively or qualitatively) can be employed to reduce very significantly the number of behaviours. An initial indication is given as to how the approach could be used to explain observed electrocardiograms (ECGs) in terms of the underlying physiological processes.