[HTML][HTML] Explainable artificial intelligence model for stroke prediction using EEG signal

MS Islam, I Hussain, MM Rahman, SJ Park… - Sensors, 2022 - mdpi.com
State-of-the-art healthcare technologies are incorporating advanced Artificial Intelligence
(AI) models, allowing for rapid and easy disease diagnosis. However, most AI models are …

[PDF][PDF] Classification of stroke patients using data mining with adaboost, decision tree and random forest models

B Imran, E Wahyudi, A Subki, S Salman… - ILKOM Jurnal …, 2022 - researchgate.net
A stroke is a fatal disease that usually occurs to the people over the age of 65. The treatment
progress of the medical field is growing rapidly, especially with the technological advance …

Classification of brain disease using deep learning with multi-modality images

J Angel Sajani, A Ahilan - Journal of Intelligent & Fuzzy …, 2023 - content.iospress.com
Brain diseases is a wide range of disorders and diseases that affect the brain. They can
change a person's behavior, personality, and capacity for thought and function. CT images …

[HTML][HTML] Electroencephalographic Characterization by Covariance Analysis in Men with Parkinson's Disease Reveals Sex-and Age-Related Differences

G González-González, VM Velasco Herrera… - Applied Sciences, 2023 - mdpi.com
Parkinson's disease (PD) is the fastest growing neurological disease associated with
ageing; its symptomatology varies between sexes. Several quantitative …

[PDF][PDF] An Ensemble Deep Learning Network in Classifying the Early CT Slices of Ischemic Stroke Patients.

K Rajendran, M Radhakrishnan… - Traitement du …, 2022 - academia.edu
Accepted: 2 August 2022 The human brain is the body's most complicated organ. Constant
blood flow is essential for the sustained functioning of the brain. A blocked blood vessel's …

Classification of ischemic and hemorrhagic stroke using Enhanced-CNN deep learning technique

M Shakunthala, K HelenPrabha - Journal of Intelligent & …, 2023 - content.iospress.com
Stroke is a type of cerebrovascular disorder that has a significant impact on people's lives
and well-being. Quantitative investigation of MRI imaging of the brain plays a critical role in …

A Review on Image Classification Techniques for MRI Brain Stroke Lesion

NM Saad, AR Abdullah, IH Azman… - Journal of Advanced …, 2024 - semarakilmu.com.my
A stroke, a fatal brain disorder with systemic consequences, emphasizes the crucial need of
timely treatment. Recent studies emphasize the" time is brain" notion, which states that …

Blood stroke Classification using Proposed CNN Model

R Singh, N Sharma, H Gupta - 2023 World Conference on …, 2023 - ieeexplore.ieee.org
The faster medical treatment is provided, the better chances of recovery from a blood stroke.
Early detection allows for prompt medical intervention, which can aid in the dissolution of the …

Modified ResNet152v2: Binary Classification and Hybrid Segmentation of Brain Stroke Using Transfer Learning-Based Approach

N Parimala, G Muneeswari - Polish Journal of Medical Physics and …, 2024 - sciendo.com
Results: Per the performance analysis, the proposed approach outperformed the other deep
learning algorithms, achieving the best accuracy of 99.25%, sensitivity of 99.65%, F1-score …

[HTML][HTML] Feature Fusion-based Brain Stroke Identification Model Using Computed Tomography Images

AW Abulfaraj, AK Dutta, ARW Sait - Journal of Disability …, 2024 - scienceopen.com
Accurate and rapid diagnosis is essential in the healthcare system for the detection of
strokes to mitigate the devastating effects. This study introduces an innovative model for …