Pattern Recognition Intelligent System Based RTF-NNT For Early Detection: Application on Alzheimer

Abstract

The recognition of the interrelationship between science and mathematics led to the creation of a new concept called artificial intelligence (AI) which contributed to solve many outstanding problems. Artificial Intelligence is the new frontier of health research and development. In this paper Artificial Intelligence challenges Alzheimer. The aim of this study is to use artificial intelligence tools to track various Alzheimer’s stages and symptoms over time and according to the patients. In order to achieve this efficient pattern recognition intelligent system based time-frequency representation-neural networks (RTF-NNT) extracts and classifies a large number of Alzheimer’s features. Each of them is associated, or not, with a pathological state, which makes it possible to automatically classify patients in diagnostic categories. This intelligent system also allows enriching the health database; which areas are altered? Which patients develop Alzheimer’s disease? How long? So much data will be crossed then in the hope of "predicting the evolution of neurodegenerative diseases, such as Alzheimer’s, at very early stages, ten or twenty years. As a stimulating result, AI tools can be adopted to promote health, reduce the time and early automatic detection of Alzheimer’s. Refine the diagnosis and predict the evolution.