Machine learning applied to diagnosis of human diseases: A systematic review
N Caballé-Cervigón, JL Castillo-Sequera… - Applied Sciences, 2020 - mdpi.com
Human healthcare is one of the most important topics for society. It tries to find the correct
effective and robust disease detection as soon as possible to patients receipt the …
effective and robust disease detection as soon as possible to patients receipt the …
A comprehensive review on detection and classification of dementia using neuroimaging and machine learning
N Pateria, D Kumar - Multimedia Tools and Applications, 2024 - Springer
Dementia, not a particular disease but rather a gathering of conditions which ascribes the
debilitation of atleast two cerebrum capacities, cognitive decline and memory judgment has …
debilitation of atleast two cerebrum capacities, cognitive decline and memory judgment has …
Computer-aided automated discrimination of Alzheimer's disease and its clinical progression in magnetic resonance images using hybrid clustering and game theory …
Early detection and identification of morphological differences in the brain is crucial for the
pre-surgical planning of Alzheimer's disease treatment. Magnetic resonance imaging (MRI) …
pre-surgical planning of Alzheimer's disease treatment. Magnetic resonance imaging (MRI) …
MR Brain image segmentation for the volumetric measurement of tissues to differentiate Alzheimer's disease using hybrid algorithm
T Arunprasath, MP Rajasekaran… - … on Clean Energy …, 2019 - ieeexplore.ieee.org
Structural variation in MR brain image is an essential tool to identify Alzheimer's disease
(AD). Gray matter reduction, cortical thickness and the volume of hippocampal which have …
(AD). Gray matter reduction, cortical thickness and the volume of hippocampal which have …
Brain subject segmentation in MR image for classifying Alzheimer's disease using AdaBoost with information fuzzy network classifier
P Rajesh Kumar, T Arun Prasath… - Soft Computing in Data …, 2019 - Springer
Alzheimer's disease (AD) is a neurodegenerative brain disorder which develops gradually
over several years of time period. It is not always understandable at initially because which …
over several years of time period. It is not always understandable at initially because which …
Biomedical Image Data Segmentation with Using of Clustering Driven by Genetic Algorithms
The clustering algorithms, like is the K-means algorithm, are commonly utilized for the
biomedical image regional segmentation. One of the major limitations of the clustering …
biomedical image regional segmentation. One of the major limitations of the clustering …
Decisive Tissue Segmentation in MR Images: Classification Analysis of Alzheimer's Disease Using Patch Differential Clustering
P Rajesh Kumar, T Arun Prasath… - Proceedings of the 2nd …, 2019 - Springer
Alzheimer's disease usually occurs in the elderly, and over a course period of time, it
contributes to dementia. Substantiation of cerebrovascular disease progressively develops …
contributes to dementia. Substantiation of cerebrovascular disease progressively develops …
[PDF][PDF] A REVIEW PAPER ON AUTOMATED BRAIN TUMOR DETECTION AND SEGMENTATION BY USING CLUSTERING TECHNIQUES
JG AHIRRAO, VS KARWANDE - oaijse.com
Image segmentation has historically been thought of as the first step in image processing. A
good segmentation result will make further image processing analysis much simpler …
good segmentation result will make further image processing analysis much simpler …