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Early-stage Alzheimer's disease prediction using machine learning models
C Kavitha, V Mani, SR Srividhya, OI Khalaf… - Frontiers in public …, 2022 - frontiersin.org
Alzheimer's disease (AD) is the leading cause of dementia in older adults. There is currently
a lot of interest in applying machine learning to find out metabolic diseases like Alzheimer's …
a lot of interest in applying machine learning to find out metabolic diseases like Alzheimer's …
Denouements of machine learning and multimodal diagnostic classification of Alzheimer's disease
Alzheimer's disease (AD) is the most common type of dementia. The exact cause and
treatment of the disease are still unknown. Different neuroimaging modalities, such as …
treatment of the disease are still unknown. Different neuroimaging modalities, such as …
[PDF][PDF] A novel approach of CT images feature analysis and prediction to screen for corona virus disease (COVID-19)
AA Farid, GI Selim, HAA Khater - Preprints, 2020 - academia.edu
The paper demonstrates the analysis of Corona Virus Disease based on a probabilistic
model. It involves a technique for classification and prediction by recognizing typical and …
model. It involves a technique for classification and prediction by recognizing typical and …
Comparative analysis of various machine learning algorithms for detecting dementia
Nowadays, there has been recent interest in applying machine learning techniques to the
neurodegenerative disorders. Dementia is one such emerging global health issue and its …
neurodegenerative disorders. Dementia is one such emerging global health issue and its …
A survey on classification algorithms of brain images in Alzheimer's disease based on feature extraction techniques
Alzheimer's disease (AD) is one of the most serious neurological disorders for elderly
people. AD affected patient experiences severe memory loss. One of the main reasons for …
people. AD affected patient experiences severe memory loss. One of the main reasons for …
Performance of classification based on PCA, linear SVM, and Multi-kernel SVM
Many studies are based on automatic or semi-automatic measurement of various a priori
brain Region of Interest (ROI) to compare and discriminate between healthy controls (HC) …
brain Region of Interest (ROI) to compare and discriminate between healthy controls (HC) …
Classification of magnetic resonance images using bag of features for detecting dementia
In this paper, a model is presented for classification of Dementia brain disease using
magnetic resonance imaging. Bag of features (BOF) is used for extracting the features of …
magnetic resonance imaging. Bag of features (BOF) is used for extracting the features of …
[HTML][HTML] Alzheimer's disease early diagnosis using manifold-based semi-supervised learning
M Khajehnejad, F Habibollahi Saatlou… - Brain sciences, 2017 - mdpi.com
Alzheimer's disease (AD) is currently ranked as the sixth leading cause of death in the
United States and recent estimates indicate that the disorder may rank third, just behind …
United States and recent estimates indicate that the disorder may rank third, just behind …
[PDF][PDF] Applying artificial intelligence techniques for prediction of neurodegenerative disorders: A comparative case-study on clinical tests and neuroimaging tests with …
Alzheimer's disease (AD) detection acting as an essential role in global health care due to
misdiagnosis and sharing many clinical sets with other types of dementia, and costly …
misdiagnosis and sharing many clinical sets with other types of dementia, and costly …
[PDF][PDF] Applying artificial intelligence techniques to improve clinical diagnosis of Alzheimer's disease
AA Farid, GI Selim, HAA Khater - European Journal of …, 2020 - researchgate.net
Alzheimer's disease (AD) is a significant regular type of dementia that causes damage in
brain cells. Early detection of AD acting as an essential role in global health care due to …
brain cells. Early detection of AD acting as an essential role in global health care due to …