Department of College of Computer Science, King Khalid University, Abh, Saudi Arabia
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Detecting Alzheimer's disease using a Hybrid Deep Learning Approach
Author(s): Meraj Riga*
Alzheimer's disease primarily affects the nervous system. Neuronal atrophy, amyloid deposition, and cognitive,
behavioural, and mental problems are the main hallmarks. Over the years, a variety of machine learning algorithms
have been studied and used for identification, focusing on the subtle prodromal stage of mild cognitive impairment
to evaluate key characteristics that distinguish the disease's early manifestation and provide guidance for early
detection and treatment. Due to the difficulties in telling individuals with cognitive normalcy from from those
without, early identification is still difficult. The majority of classification algorithms thus perform badly for these
two categories. For the purpose of Alzheimer's disease early detection, this research suggests a hybrid Deep Learning
Approach. Combining multimodal imagery with a convolutional neur.. View more»