Abstract
This article presents the development of an expert system on detection, evaluation and treatment of hypertension (high blood pressure), together with an outline of the associated computational processes. It has been implemented on the computer algebra system Maple.
The starting point is the knowledge about detection of major cardiovascular disease (CVD) risk and about detection, evaluation and treatment of hypertension, provided in table and algorithm format by experts from some well known medical societies and committees. As the drug choices for treating hypertension depends on whether the patient suffers, among other diseases, from high CVD risk or not, the expert system consists of two consecutive subsystems. The first one determines the CVD risk level, meanwhile the second one uses the output of the first one to detect, evaluate and, if necessary, suggest a treatment of hypertension.
The knowledge expressed by the experts was revised and reorganized by the authors. Curiously, some errata were found in some of the classifications provided in table format.
The computational processes involved are simple because the cases are already separated (disjoint), so they can be translated into IF...THEN... rules that can be applied using classifications in simple procedures.Therefore, verification is restricted to considering a few cases (the conjunction of all diseases together with different CDV risks). Nevertheless, we think this is a very useful piece of software for practitioners, because, to reach, for instance, the treatment of hypertension, several messy concatenated steps have to be taken.
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Roanes-Lozano, E., López-Vidriero, E., Laita, L.M., López-Vidriero, E., Maojo, V., Roanes-Macías, E. (2004). An Expert System on Detection, Evaluation and Treatment of Hypertension. In: Buchberger, B., Campbell, J. (eds) Artificial Intelligence and Symbolic Computation. AISC 2004. Lecture Notes in Computer Science(), vol 3249. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30210-0_21
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