Abstract:
Mild Cognitive Impairment (MCI) [1] is an early stage of Alzheimer’s disease (AD)
with increased growth rate around the globe. It effects human’s cognitive ability
and memory. It has no cure, once a person is affected. However, if early symptoms
are diagnosed timely then it can be avoided or its growth rate could be slow down
using medication. An early symptoms indication of AD is called Mild Cognitive
Impairment (MCI). Lack of distinct medical cure for this disease have urged the
need to identify factors of early diagnosis of AD using automated process. Its
common symptoms include cognitive impairment, memory loss, difficulty in
thinking and understanding words, and inability to identify family members.
Moreover, lack of Beta proteins and CDR [(Clinical Dementia Rating)] code in
MRI (Magnetic Resonance Imaging) scans are important Clinical data parameters
[1].
Identification of MCI using MRI scans of ADNI dataset is less prone to
errors as MRI generate quality medical images [1]. This project aims to diagnose
MCI using CNN (Convolution Neural Network) applied on MRI scans [1]. This
project will be implemented in Python programming language using PyCharm and
will provide services through an online web-based Interface. Web interface will be
built using FLASK framework, HTML, CSS and Bootstrap. Machine learning
training will be performed using python machine learning libraries such as SICKIT
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