Using discrete optimization tools to classify cognitive deficits: special aspects of using the minimax and additive criterion

The paper devoted to the development of discrete optimization methods for solving the applied problem of clustering the cognitive resources of patients with coronary artery disease (CAD). The methods reflect the prospects of their surgical treatment. Many indicators of different cognitive functions and brain activity are used to determine the cognitive deficits associated with aging and concomitant cerebrovascular atherosclerosis. Coronary artery bypass grafting, which is widely used to treat CAD patients, increases the risk of postoperative cognitive deficits. In this regard, it is important to identify the most informative markers of the cognitive status in patients in the preoperative state. To classify this state, the authors use the hemispheric activity characteristics, i.e. lateralized power of the theta, alpha, and beta rhythms together with the indicator of minimal cerebral dysfunction (MMSE) and the integral cognitive indicator based on a set of parameters obtained during a recording sensorymotor responses and testing attention and memory in 114 male patients admitted to the clinic for coronary artery bypass grafting. The average patient's age is 55.9 ± 5.3 years; 90 of them had secondary education and 32 had higher education. The results of computational experiments with clustering indicators of psychometric and neuro-physiological testing of CAD patients have shown the effectiveness of the developed toolkit for clustering by the discrete optimization means and the best discriminatory capabilities due to the additive criterion.