Improved diagnosis of Parkinson's disease using optimized crow search algorithm
Diagnosis of Parkinson's disease at its early stage is important in proper treatment of the
patients so they can lead productive lives for as long as possible. Although many techniques …
patients so they can lead productive lives for as long as possible. Although many techniques …
Diagnosis of Parkinson's disease using modified grey wolf optimization
This paper presents the Modified Grey Wolf Optimization (MGWO) algorithm which helps
with the identification of the symptoms of Parkinson's disease at a premature stage …
with the identification of the symptoms of Parkinson's disease at a premature stage …
CROWD: crow search and deep learning based feature extractor for classification of Parkinson's disease
Edge Artificial Intelligence (AI) is the latest trend for next-generation computing for data
analytics, particularly in predictive edge analytics for high-risk diseases like Parkinson's …
analytics, particularly in predictive edge analytics for high-risk diseases like Parkinson's …
Optimized cuttlefish algorithm for diagnosis of Parkinson's disease
This paper presents an optimized cuttlefish algorithm for feature selection based on the
traditional cuttlefish algorithm, which can be used for diagnosis of Parkinson's disease at its …
traditional cuttlefish algorithm, which can be used for diagnosis of Parkinson's disease at its …
Feature selection and classification using CatBoost method for improving the performance of predicting Parkinson's disease
Several studies investigated the diagnosis of Parkinson's disease (PD), which utilized
machine learning methods such as support vector machine, neural network, Naïve Bayes …
machine learning methods such as support vector machine, neural network, Naïve Bayes …
Feature selection based machine learning to improve prediction of Parkinson disease
Parkinson's disease (PD) is a kind of neurodegenerative disorder characterized by the loss
of dopamine-producing cells in the brain. The disruption of brain cells that create dopamine …
of dopamine-producing cells in the brain. The disruption of brain cells that create dopamine …
Binary grey wolf optimizer with mutation and adaptive k-nearest neighbour for feature selection in Parkinson's disease diagnosis
RR Rajammal, S Mirjalili, G Ekambaram… - Knowledge-Based …, 2022 - Elsevier
Disease identification and classification relies on Feature Selection (FS) to find the relevant
features for accurate medical diagnosis. FS is an optimization problem solved with the help …
features for accurate medical diagnosis. FS is an optimization problem solved with the help …
A survey of nature-inspired algorithms for feature selection to identify Parkinson's disease
P Shrivastava, A Shukla, P Vepakomma… - Computer methods and …, 2017 - Elsevier
Abstract Background and Objectives Parkinson's disease is a chronic neurological disorder
that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and …
that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and …
Feature selection via a novel chaotic crow search algorithm
Crow search algorithm (CSA) is a new natural inspired algorithm proposed by Askarzadeh
in 2016. The main inspiration of CSA came from crow search mechanism for hiding their …
in 2016. The main inspiration of CSA came from crow search mechanism for hiding their …
A comparative study of existing machine learning approaches for Parkinson's disease detection
G Pahuja, TN Nagabhushan - IETE Journal of Research, 2021 - Taylor & Francis
Parkinson's disease (PD) has affected millions of people worldwide and is more prevalent in
people, over the age of 50. Even today, with many technologies and advancements, early …
people, over the age of 50. Even today, with many technologies and advancements, early …