Neurophysiological markers of early cognitive decline in older adults: a mini-review of electroencephalography studies for precursors of dementia

M Tanaka, E Yamada, F Mori - Frontiers in Aging Neuroscience, 2024 - frontiersin.org
The early detection of cognitive decline in older adults is crucial for preventing dementia.
This mini-review focuses on electroencephalography (EEG) markers of early dementia …

[HTML][HTML] Alzheimer's disease detection from fused PET and MRI modalities using an ensemble classifier

A Shukla, R Tiwari, S Tiwari - Machine Learning and Knowledge …, 2023 - mdpi.com
Alzheimer's disease (AD) is an old-age disease that comes in different stages and directly
affects the different regions of the brain. The research into the detection of AD and its stages …

Improvement of machine learning models' performances based on ensemble learning for the detection of Alzheimer disease

S Buyrukoğlu - 2021 6th International Conference on Computer …, 2021 - ieeexplore.ieee.org
Failure to early detection of Alzheimer's disease (AD) can lead memory deterioration.
Therefore, early detection of AD is essential affecting the points of the brain that control vital …

Alz-ConvNets for classification of Alzheimer disease using transfer learning approach

A Shukla, R Tiwari, S Tiwari - SN Computer Science, 2023 - Springer
Alzheimer disease (AD) is a progressive brain disorder that gradually deprives patients of
their basic abilities. Despite the absence of specific treatments, early detection of this …

[PDF][PDF] Students performance: From detection of failures and anomaly cases to the solutions-based mining algorithms

EI Al-Fairouz, MA Al-Hagery - Int. J. Eng. Res. Technol, 2020 - researchgate.net
Abstract Educational Data Mining (EDM) helps to recognise the performance of students and
predict their academic achievements that include the successes aspects and failures …

Graph neural network based Alzheimer's disease classification using structural brain network

S Subaramya, T Kokul, R Nagulan… - … on Advances in ICT …, 2022 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a chronic, incurable disorder that worsens with time and
requires early diagnosis in order to treat and manage AD patients. Diffusion MR imaging …

[PDF][PDF] Comparison of resting electroencephalogram coherence in patients with mild cognitive impairment and normal elderly

S Hadiyoso, I Wijayanto, S Aulia - International Journal of Electrical …, 2022 - academia.edu
Mild cognitive impairment (MCI) was a condition beginning before more serious
deterioration, leading to Alzheimer's dementia (AD). MCI detection was needed to determine …

Analysis of ensemble machine learning classification comparison on the skin cancer MNIST dataset

PLL Belluano, RA Rahma, H Darwis… - Computer Science and …, 2024 - iaesprime.com
This study aims to analyze the performance of various ensemble machine learning methods,
such as Adaboost, Bagging, and Stacking, in the context of skin cancer classification using …

Alzheimer's Disease (AD) Detection Using Various Machine Learning Techniques: A Systematic Review

A Saxena, H Kaur - 2023 6th International Conference on …, 2023 - ieeexplore.ieee.org
Alzheimer “s disease (AD) is a chronic and irreversible brain illness for which no effective
treatment exists. However, available medicines can only slow the progress of the disease …

Forecasting Carbon Dioxide Emission in Thailand Using Machine Learning Techniques

S Chimphlee, W Chimphlee - Indonesian Journal of …, 2023 - section.iaesonline.com
Abstract Machine Learning (ML) models and the massive quantity of data accessible provide
useful tools for analyzing the advancement of climate change trends and identifying major …