Two-stage classifier for diagnosis of hypertension type

The inductive learning approach could be immensely useful as the method generating effective classifiers. This paper presents idea of constructing two-stage classifier for diagnosis of the type of hypertension (essential hypertension and five type of secondary one: fibroplastic renal artery stenosis, atheromatous renal artery stenosis, Conn's syndrome, renal cystic disease and pheochromocystoma). The first step decides if patient suffers from essential hypertension or secondary one. This decision is made on the base on the decision of classifier obtained by boosted version of additive tree algorithm. The second step of classification decides which type of secondary hypertension patient is suffering from. The second step of classifier makes its own decision using human expert rules. The decisions of these classifiers are made only on base on blood pressure, general information and basis biochemical data.