Abstract
The knowledge employed by a cardiologist in the interpretation of an electrocardiogram (ECG) can be represented by means of a system of conditional attributed rewriting rules (calL-systems), a generative device introduced in (1) which has been successfully applied in other experiments (2,3,4). Each rule codes a chunk of knowledge necessary to recognize a structure in the ECG and evaluate its characteristics. Attributed rewriting systems have been proposed in (5) to overcome the limitations of the statistical and syntactical approaches to pattern recognition which were both used separately for ECG interpretation (6,7). This coding of the physician’s knowledge allows one to derive a Pattern Directed Inference System (PDIS) (8) able to describe the ECG at hand. Once the ECG is described, the descriptions can be stored in an Information Retrieval System and retrieved even by combination of characteristics not foreseen by the developer of the system, but which can be of interest to a physician in the case at hand.
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Bottoni, P., Cigada, M., De Giuli, A., Di Cristofaro, B., Mussio, P. (1989). Attributed Conditional Rewriting Systems as a Tool for ECG Description and Interpretation. In: Hunter, J., Cookson, J., Wyatt, J. (eds) AIME 89. Lecture Notes in Medical Informatics, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-93437-7_9
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DOI: https://doi.org/10.1007/978-3-642-93437-7_9
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