Predicting Alzheimer’s Disease Progression through Machine Learning Algorithms DOI

Mekhala Bharath,

S. Gowtham,

S Vedanth

et al.

Published: Nov. 23, 2023

This study revolves around the crucial task of early Alzheimer's disease (AD) detection using machine learning algorithms. Leveraging a dataset 6400 preprocessed MRI images, research rigorously evaluates spectrum models, encompassing Support Vector Machines (SVM) with diverse kernels, multidimensional Linear Discriminant Analysis (LDA), comprehensive Principal Component (PCA), and Convolutional Neural Networks (CNN) integrated within architecture EfficientNetB0. Significantly, SVM model, utilizing linear kernel, emerges as standout performer, achieving an impressive accuracy 98% in AD remarkable 98.7% classification. These findings distinctly underscore efficacy particularly when harnessed potent tools for precise

Language: Английский

Predictive Modeling for Cirrhosis Diagnosis: A Machine Learning Exploration DOI

Sudeesh Kumar,

B Natarajan,

Pavankumar Murali

et al.

Published: May 2, 2024

Language: Английский

Citations

0
Analysis of Skin Lesion Classification using Computational Models DOI

Chalana B Arun,

M. Anusha,

Trupthi Rao

et al.

Published: July 26, 2024

Language: Английский

Citations

0
Real-Time House Price Predictions with Regression Analysis DOI

K Purushotham,

Bangarappa,

Ashwini Kodipalli

et al.

Published: May 16, 2024

Language: Английский

Citations

0
Predicting Alzheimer’s Disease Progression through Machine Learning Algorithms DOI

Mekhala Bharath,

S. Gowtham,

S Vedanth

et al.

Published: Nov. 23, 2023

This study revolves around the crucial task of early Alzheimer's disease (AD) detection using machine learning algorithms. Leveraging a dataset 6400 preprocessed MRI images, research rigorously evaluates spectrum models, encompassing Support Vector Machines (SVM) with diverse kernels, multidimensional Linear Discriminant Analysis (LDA), comprehensive Principal Component (PCA), and Convolutional Neural Networks (CNN) integrated within architecture EfficientNetB0. Significantly, SVM model, utilizing linear kernel, emerges as standout performer, achieving an impressive accuracy 98% in AD remarkable 98.7% classification. These findings distinctly underscore efficacy particularly when harnessed potent tools for precise

Language: Английский

Citations

1