Data Mining and decision support systems for clinical application and quality of life

The development of new technologies, information systems, decision support systems and clinical parameters prediction algorithms using machine learning and data mining, opens a new outlook in many areas of health. In this context, the concept of Quality of Life (QOL) has relevance in health and the possibility of integrate this measure in developing systems Decision Support Clinic (SADC). Through individual expectation of physical well-being, psychological, mental, emotional and spiritual patient, clinical variables and quality of life assessment, we intend to make a study of data to establish correlations with clinical data and pharmaceutical data, socio-economic factors, among others, for obtaining knowledge in terms of behavioral patterns of chronically ill, reaching a number of reliable data and easily accessible, capable of enhancing the decision-making process on the part of specialist medical teams, seeking to improve treatments and consequently the quality of life related to health chronically ill. This paper studied and compared related studies that develop systems for decision support and prediction in the clinical area, with emphasis on studies in the area of quality of life.

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