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Alzheimer’s disease(AD) is a neurological disease. It affects memory. The livelihood of the people that are diagnosed with AD. In this paper, we have discussed various imaging modalities, feature selection and extraction, segmentation and classification techniques.
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In this work, the TREPAN algorithm is enhanced and extended for extracting decision trees from neural networks. We empirically evaluated the performance of the algorithm on a set of databases from real world events. This benchmark enhancement was achieved by adapting Single-test TREPAN and C4.5 decision tree induction algorithms to analyze the datasets. The models are then compared with X-TREPAN for comprehensibility and classification accuracy. Furthermore, we validate the experimentations by applying statistical methods. Finally, the modified algorithm is extended to work with multi-class regression problems and the ability to comprehend generalized feed forward networks is achieved.
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Alzheimer’s disease(AD) is a neurological disease. It affects memory. The livelihood of the people that are diagnosed with AD. In this paper, we have discussed various imaging modalities, feature selection and extraction, segmentation and classification techniques.
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All estimates, opinions and plans provided in this document are based on the best information available at the time of the creation of this document on May 10, 2016 and we do not guarantee their accuracy. Therefore our actual results may differ due to various unforeseen risk factors and changes in global economies.
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