A novel computational model for ECG diagnostic justification may be a feasible tool for teaching and evaluating medical students in electrocardiography.
A novel hybrid structural-parametric model for ECG diagnostic justification is presented in the paper. In order to distinguish between specific subclasses of heart dysfunction phenomena both grammars and automata are enhanced with a formalism of dynamic programming. It allows one to construct a system, which is feasible for aiding a process of teaching and evaluating medical students' diagnostic reasoning in the area of electrocardiography.
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Piotr Flasiński (2014) studied ECG abnormalities (e.g., AV blocks). Dynamically programmed attributed regular grammar (DPARG) and automaton (DPAFSA) vs. Programmed attributed regular grammar (PARG) and automaton (PAFSA) was evaluated on Differentiation between specific subclasses of heart dysfunction phenomena (e.g., Mobitz I and Mobitz II).
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