Diagnosis of Alzheimer's Disease using Machine Learning

被引：0
|
作者：
Lodha, Priyanka [1 ]
Talele, Ajay [1 ]
Degaonkar, Kishori [1 ]
机构：
[1] Vishwakarma Inst Technol, Dept EnTC, Pune, Maharashtra, India
来源：
2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA) | 2018年
关键词：
Linear Regression; Machine Learning algorithm; Alzheimer's disease symptoms; Random Forest; Gradient Boosting Algorithm; Neural Network; SVM FEATURE-SELECTION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Machine learning is being widely used in various medical fields. Advances in medical technologies have given access to better data for identifying symptoms of various diseases in early stages. Alzheimer's disease is chronic condition that leads to degeneration of brain cells leading at memory enervation. Patients with cognitive mental problems such as confusion and forgetfulness, also other symptoms including behavioral and psychological problems are further suggested having CT, MRI, PET, EEG, and other neuroimaging techniques. The aim of this paper is making use of machine learning algorithms to process this data obtained by neuroimaging technologies for detection of Alzheimer's in its primitive stage.
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页数：4
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