Predicting patients with Parkinson's disease using Machine Learning and ensemble voting technique
Parkinson's disease is the second most common neurological disorder that causes
significant physical disabilities, decreases the quality of life, and does not have a cure …
significant physical disabilities, decreases the quality of life, and does not have a cure …
Parkinson Risks Determination Using SVM Coupled Stacking
S Dutta, S Choudhury, A Chakraborty, S Mishra… - International Conference …, 2023 - Springer
Biomarkers obtained from a person's voice may provide interpretations into brain-related
risks like Parkinson's disease due to their cognitive aspects. This audit portrays as of late …
risks like Parkinson's disease due to their cognitive aspects. This audit portrays as of late …
[HTML][HTML] Electroencephalography (EEG) eye state classification using learning vector quantization and bagged trees
The analysis of Electroencephalography (EEG) signals has been an effective way of eye
state identification. Its significance is highlighted by studies that examined the classification …
state identification. Its significance is highlighted by studies that examined the classification …
Diagnosis of parkinson's disease based on voice signals using SHAP and hard voting ensemble method
Parkinson's disease (PD) is the second most common progressive neurological condition
after Alzheimer's. The significant number of individuals afflicted with this illness makes it …
after Alzheimer's. The significant number of individuals afflicted with this illness makes it …
[HTML][HTML] Parkinson's disease diagnosis using Laplacian score, Gaussian process regression and self-organizing maps
Parkinson's disease (PD) is a complex degenerative brain disease that affects nerve cells in
the brain responsible for body movement. Machine learning is widely used to track the …
the brain responsible for body movement. Machine learning is widely used to track the …
A new Diagnosis using a Parkinson's Disease XGBoost and CNN-based classification model Using ML Techniques
Parkinson's disease (PD) is a neurological condition that affects the brain of the human body
and causes difficultywalking, shaking, stiffness, and loss of balance and coordination. Most …
and causes difficultywalking, shaking, stiffness, and loss of balance and coordination. Most …
Accuracy Analysis of Type-2 Fuzzy System in Predicting Parkinson's Disease Using Biomedical Voice Measures
Parkinson's disease (PD) is a progressive neurodegenerative illness triggered by decreased
dopamine secretion. Fuzzy logic has gained substantial attention in PD diagnosis research …
dopamine secretion. Fuzzy logic has gained substantial attention in PD diagnosis research …
Interpretable stroke risk prediction using machine learning algorithms
N Zafeiropoulos, A Mavrogiorgou, S Kleftakis… - … : Selected Papers of …, 2023 - Springer
Stroke is the second most common cause of death globally according to the World Health
Organization (WHO). Information Technology (IT), and especially Machine Learning (ML) …
Organization (WHO). Information Technology (IT), and especially Machine Learning (ML) …
[HTML][HTML] Unveiling Research Trends: A Decade-long Analysis of Academic Research (2013-2024)
M Nilashi - Journal of Soft Computing and Decision Support …, 2023 - jscdss.com
This work analyzes papers published between 2013 and 2024, as reported by the Scopus
database. The examination focuses on my collaborative contributions within this timeframe …
database. The examination focuses on my collaborative contributions within this timeframe …
Weighted heterogeneous ensemble for the classification of intrusion detection using ant colony optimization for continuous search spaces
D Albashish, A Aburomman - Soft Computing, 2023 - Springer
This paper proposes a heterogeneous ensemble classifier configuration for a multiclass
intrusion detection problem. The ensemble is composed of k-nearest neighbors, artificial …
intrusion detection problem. The ensemble is composed of k-nearest neighbors, artificial …