Machine learning techniques for the diagnosis of Alzheimer's disease: A review
Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …
elderly population. Efficient automated techniques are needed for early diagnosis of …
Knowledge discovery in medicine: Current issue and future trend
N Esfandiari, MR Babavalian, AME Moghadam… - Expert Systems with …, 2014 - Elsevier
Data mining is a powerful method to extract knowledge from data. Raw data faces various
challenges that make traditional method improper for knowledge extraction. Data mining is …
challenges that make traditional method improper for knowledge extraction. Data mining is …
On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey
Abstract Introduction The number of Alzheimer's Disease (AD) patients is increasing with
increased life expectancy and 115.4 million people are expected to be affected in 2050 …
increased life expectancy and 115.4 million people are expected to be affected in 2050 …
Computer-aided diagnosis: A survey with bibliometric analysis
R Takahashi, Y Kajikawa - International journal of medical informatics, 2017 - Elsevier
Computer-aided diagnosis (CAD) has been a promising area of research over the last two
decades. However, CAD is a very complicated subject because it involves a number of …
decades. However, CAD is a very complicated subject because it involves a number of …
From data science to bioscience: emerging era of bioinformatics applications, tools and challenges
With the gradual technological changes in the current era, data science using soft computing
and machine learning methods has played a tremendous role in various areas, including the …
and machine learning methods has played a tremendous role in various areas, including the …
Two fully-unsupervised methods for MR brain image segmentation using SOM-based strategies
Image segmentation consists in partitioning an image into different regions. MRI image
segmentation is especially interesting, since an accurate segmentation of the different brain …
segmentation is especially interesting, since an accurate segmentation of the different brain …
Automatic assistance to Parkinsonˈs disease diagnosis in DaTSCAN SPECT imaging
Purpose: In this work, an approach to computer aided diagnosis (CAD) system is proposed
as a decision‐making aid in Parkinsonian syndrome (PS) detection. This tool, intended for …
as a decision‐making aid in Parkinsonian syndrome (PS) detection. This tool, intended for …
Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares
Background Alzheimer's disease (AD) is the most common cause of dementia in the elderly
and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) …
and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) …
Stacked deep dense neural network model to predict alzheimer's dementia using audio transcript data
Alzheimer's disease (AD) is caused by cortical degeneration leading to memory loss and
dementia. A possible criterion for the early identification of Alzheimer's dementia is to identify …
dementia. A possible criterion for the early identification of Alzheimer's dementia is to identify …
A novel method for early diagnosis of Alzheimer's disease based on pseudo Zernike moment from structural MRI
HT Gorji, J Haddadnia - Neuroscience, 2015 - Elsevier
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most
common type of dementia among older people. The number of patients with AD will grow …
common type of dementia among older people. The number of patients with AD will grow …