Parkinson's disease diagnosis using neural networks: Survey and comprehensive evaluation
Parkinson's disease (PD) is a chronic neurodegenerative disease of that predominantly
affects the elderly in today's world. For the diagnosis of the early stages of PD, effective and …
affects the elderly in today's world. For the diagnosis of the early stages of PD, effective and …
Cartesian genetic programming: its status and future
JF Miller - Genetic Programming and Evolvable Machines, 2020 - Springer
Cartesian genetic programming, a well-established method of genetic programming, is
approximately 20 years old. It represents solutions to computational problems as graphs. Its …
approximately 20 years old. It represents solutions to computational problems as graphs. Its …
Disease diagnosis using machine learning techniques: A review and classification
In this research, we reviewed and classified academic conference and journal papers; which
used data mining techniques in disease classification and diagnosis based on public …
used data mining techniques in disease classification and diagnosis based on public …
Early diagnosis of Parkinson's disease: A combined method using deep learning and neuro-fuzzy techniques
Abstract Predicting Unified Parkinson's Disease Rating Scale (UPDRS) in Total-UPDRS and
Motor-UPDRS clinical scales is an important part of controlling PD. Computational …
Motor-UPDRS clinical scales is an important part of controlling PD. Computational …
Robust ensemble classification methodology for I123-Ioflupane SPECT images and multiple heterogeneous biomarkers in the diagnosis of Parkinson's disease
In last years, several approaches to develop an effective Computer-Aided-Diagnosis (CAD)
system for Parkinson's Disease (PD) have been proposed. Most of these methods have …
system for Parkinson's Disease (PD) have been proposed. Most of these methods have …
An analytical method for measuring the Parkinson's disease progression: A case on a Parkinson's telemonitoring dataset
The use of machine learning techniques for early diseases diagnosis has attracted the
attention of scholars worldwide. Parkinson's Disease (PD) is one of the most common …
attention of scholars worldwide. Parkinson's Disease (PD) is one of the most common …
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 …
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 …
Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming
Abstract Wavelet Neural Networks (WNNs) are complex artificial neural systems and their
training can be a challenge. In the past, most common training schemes for WNNs, such as …
training can be a challenge. In the past, most common training schemes for WNNs, such as …
Utility and accuracy of perceptual voice and speech distinctions in the diagnosis of Parkinson's disease, PSP and MSA-P
Aim: To determine if perceptual speech measures distinguish people with Parkinson's
disease (PD), multiple system atrophy with predominant parkinsonism (MSA-P) and …
disease (PD), multiple system atrophy with predominant parkinsonism (MSA-P) and …