Abstract
Differential and early diagnosis of cognitive impairment (CI) continues being one of the crucial points to which clinical medicine faces at every level of attention, and a significant public health concern. This work proposes new CI diagnostic tools based on a data fusion scheme, artificial neural networks and ensemble systems. Concretely we have designed a supervised HUMANN [1] with capacity of missing data processing (HUMANN-S) and a HUMANN-S ensemble system. These intelligent diagnostic systems are inside EDEVITALZH, a clinical virtual environment to assist the diagnosis and prognosis of CI, Alzheimer’s disease and other dementias. Our proposal is a personalized, predictive, preventive, and participatory-healthcare delivery system (4P-HCDS) and is an optimal solution for an e-health framework. We explore their ability presenting preliminary results on differential diagnosis of CI using neuropsychological tests from 267 consultations on 30 patients by the Alzheimer’s Patient Association of Gran Canaria.
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Báez, P.G., del Pino, M.A.P., Viadero, C.F., Araujo, C.P.S. (2009). Artificial Intelligent Systems Based on Supervised HUMANN for Differential Diagnosis of Cognitive Impairment: Towards a 4P-HCDS. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_123
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DOI: https://doi.org/10.1007/978-3-642-02478-8_123
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