A survey on evolutionary multiobjective feature selection in classification: approaches, applications, and challenges
Maximizing the classification accuracy and minimizing the number of selected features are
two primary objectives in feature selection, which is inherently a multiobjective task …
two primary objectives in feature selection, which is inherently a multiobjective task …
Imperative role of machine learning algorithm for detection of Parkinson's disease: review, challenges and recommendations
Parkinson's disease (PD) is a neurodegenerative disease that affects the neural, behavioral,
and physiological systems of the brain. This disease is also known as tremor. The common …
and physiological systems of the brain. This disease is also known as tremor. The common …
Generalizing to unseen domains: A survey on domain generalization
Machine learning systems generally assume that the training and testing distributions are
the same. To this end, a key requirement is to develop models that can generalize to unseen …
the same. To this end, a key requirement is to develop models that can generalize to unseen …
A comparative analysis of speech signal processing algorithms for Parkinson's disease classification and the use of the tunable Q-factor wavelet transform
In recent years, there has been increasing interest in the development of telediagnosis and
telemonitoring systems for Parkinson's disease (PD) based on measuring the motor system …
telemonitoring systems for Parkinson's disease (PD) based on measuring the motor system …
On the iteration complexity of hypergradient computation
We study a general class of bilevel problems, consisting in the minimization of an upper-
level objective which depends on the solution to a parametric fixed-point equation. Important …
level objective which depends on the solution to a parametric fixed-point equation. Important …
Deep learning-based Parkinson's disease classification using vocal feature sets
H Gunduz - Ieee access, 2019 - ieeexplore.ieee.org
Parkinson's Disease (PD) is a progressive neurodegenerative disease with multiple motor
and non-motor characteristics. PD patients commonly face vocal impairments during the …
and non-motor characteristics. PD patients commonly face vocal impairments during the …
Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson's disease
The patients' vocal Parkinson's disease (PD) changes could be identified early on, allowing
for management before physically incapacitating symptoms appear. In this work, static as …
for management before physically incapacitating symptoms appear. In this work, static as …
Early detection of Parkinson's disease using deep learning and machine learning
Accurately detecting Parkinson's disease (PD) at an early stage is certainly indispensable
for slowing down its progress and providing patients the possibility of accessing to disease …
for slowing down its progress and providing patients the possibility of accessing to disease …
Early detection of Parkinson's disease using machine learning
A Govindu, S Palwe - Procedia Computer Science, 2023 - Elsevier
Parkinson's disease (PD) is a neurodegenerative disorder affecting 60% of people over the
age of 50 years. Patients with Parkinson's (PWP) face mobility challenges and speech …
age of 50 years. Patients with Parkinson's (PWP) face mobility challenges and speech …
Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques
Neurodegenerative diseases have shown an increasing incidence in the older population in
recent years. A significant amount of research has been conducted to characterize these …
recent years. A significant amount of research has been conducted to characterize these …