[HTML][HTML] A novel voice classification based on Gower distance for Parkinson disease detection
Background Traditional classifier for the classification of diseases, such as K-Nearest
Neighbors (KNN), Linear Discriminant Analysis (LDA), Random Forest (RF), Logistic …
Neighbors (KNN), Linear Discriminant Analysis (LDA), Random Forest (RF), Logistic …
XEMLPD: an explainable ensemble machine learning approach for Parkinson disease diagnosis with optimized features
Parkinson's disease (PD) is a progressive neurological disorder that gradually worsens over
time, making early diagnosis difficult. Traditionally, diagnosis relies on a neurologist's …
time, making early diagnosis difficult. Traditionally, diagnosis relies on a neurologist's …
Empowering Medical Diagnosis: A Machine Learning Approach for Symptom-Based Health Checker
L Aissaoui Ferhi, M Ben Amar, F Choubani… - Mobile Networks and …, 2024 - Springer
AI-powered health checkers and apps for automated medical diagnosis have a lot of
promise for a variety of applications. During pandemics, they can lessen the need for in …
promise for a variety of applications. During pandemics, they can lessen the need for in …
PD_EBM: An Integrated Boosting Approach Based on Selective Features for Unveiling Parkinson's Disease Diagnosis With Global and Local Explanations
Early detection and characterization are crucial for treating and managing Parkinson's
disease (PD). The increasing prevalence of PD and its significant impact on the motor …
disease (PD). The increasing prevalence of PD and its significant impact on the motor …
Advanced Imaging Technologies With Ensemble Learning for Consumer Products Identification and Classification
Consumer product recognition involves utilizing computer vision (CV) and machine learning
(ML) systems for identifying and recognizing numerous consumer goods in video or image …
(ML) systems for identifying and recognizing numerous consumer goods in video or image …
A Robust Support Vector Machine Approach for Raman COVID-19 Data Classification
Recent advances in healthcare technologies have led to the availability of large amounts of
biological samples across several techniques and applications. In particular, in the last few …
biological samples across several techniques and applications. In particular, in the last few …
Parkinson disease prediction using improved crayfish optimization based hybrid deep learning
A Malathi, R Ramalakshmi, V Gandhi… - … and Health Care, 2024 - journals.sagepub.com
Background Predicting the<? show [AQ ID= GQ2 POS=-24pt]?><? show [AQ ID= GQ5 POS=
12pt]?> course of Parkinson's disease is essential for prompt diagnosis and treatment, which …
12pt]?> course of Parkinson's disease is essential for prompt diagnosis and treatment, which …
[HTML][HTML] AIoT-based embedded systems optimization using feature selection for Parkinson's disease diagnosis through speech disorders
This study aims to build a pre-diagnosis tool for predicting Parkinson's disease based on a
speech disorder which appears as a symptom in approximately 90% of people with this …
speech disorder which appears as a symptom in approximately 90% of people with this …
Hybrid Voice Spectrogram-Chromogram Based Deep Learning (HVSC-DL) Model for the Detection of Parkinson's Disease
Parkinson's disease is one of the serious neurological disorders that restricts the life quality
of individuals significantly. The changes in sound signals contain important clues for …
of individuals significantly. The changes in sound signals contain important clues for …
Advancing PD Diagnosis: Machine and Deep Learning in Neuroimaging, Vocal and Clinical Data
A Gupta, S Porus, R Sasikala - Advances in Computational …, 2024 - igi-global.com
Parkinson's Disease (PD) is a chronic and progressive neurological disorder characterized
by a range of motor and non-motor symptoms due to the degeneration of dopaminergic …
by a range of motor and non-motor symptoms due to the degeneration of dopaminergic …