Implementation of an artificial neural network on the test Barcelona workstation as a predictive model for the classification of normal, mild cognitive impairment and Alzheimer's disease subjects using the Neuronorma battery
| العنوان: | Implementation of an artificial neural network on the test Barcelona workstation as a predictive model for the classification of normal, mild cognitive impairment and Alzheimer's disease subjects using the Neuronorma battery |
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| المؤلفون: | M Cabrera-Bean, J A Lupiáñez-Pretel, N Rivera, J Peña-Casanova, C Gallego-González, G Sánchez-Benavides |
| المساهمون: | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions |
| المصدر: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Recercat. Dipósit de la Recerca de Catalunya instname |
| بيانات النشر: | Knowledge E, 2018. |
| سنة النشر: | 2018 |
| مصطلحات موضوعية: | Battery (electricity), Informàtica::Intel·ligència artificial::Aprenentatge automàtic [Àrees temàtiques de la UPC], Artificial neural network, Workstation, Computer science, business.industry, Test (assessment), law.invention, Neural networks (Computer science), PROBABILITY, Cognitive impairment, law, ARTIFICIAL NEURAL NETWORK, Machine learning, Aprenentatge automàtic, Xarxes neuronals (Informàtica), Artificial intelligence, business, TEST BARCELONA WORKSTATION, NEURONORMA battery, ALZHEIMER DISEASE, Alzheimer’s disease, Neural networks |
| الوصف: | Objective: To develop and implement an online Artificial Neural Network (ANN) that provides the probability of a subject having mild cognitive impairment (MCI) or Alzheimer’s disease (AD). Method: Different ANNs were trained using a sample of 350 controls (CONT), 75 MCI and 93 AD subjects. The ANN structure chosen was the following: (1) an input layer of 33 cognitive variables from the Neuronorma battery plus two sociodemographic variables, age and education. This layer was reduced to a 15 features input vector using Multiple Discriminant Analysis method, (2) one hidden layer with 8 neurons, and (3) three output neurons corresponding to the 3 expected cognitive states. This ANN was defined in a previous study [28]. The ANN was implemented on the web site www.test-barcelona.com (Test Barcelona Workstation) [9]. Results: When comparing CONT, MCI and AD participants, the best ANN correctly classifies up to 94,87% of the study participants. Conclusions: The online implemented ANN, delivers the probabilities (%) of belonging to the CONT, MCI and AD groups of a subject assessed using the 35 characteristics (variables) of the Neuronorma profile. This tool is a good complement for the interpretation of cognitive profiles. This technology improves clinical decision making. Keywords: Artificial Neural Network, Probability, Alzheimer disease, Test Barcelona Workstation. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4188b4ebc3999024a5b5994246586e58Test https://hdl.handle.net/2117/125203Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....4188b4ebc3999024a5b5994246586e58 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |