Internet of things technologies and machine learning methods for Parkinson's disease diagnosis, monitoring and management: a systematic review
KM Giannakopoulou, I Roussaki, K Demestichas - Sensors, 2022 - mdpi.com
Parkinson's disease is a chronic neurodegenerative disease that affects a large portion of
the population, especially the elderly. It manifests with motor, cognitive and other types of …
the population, especially the elderly. It manifests with motor, cognitive and other types of …
Application of deep learning models for automated identification of Parkinson's disease: A review (2011–2021)
Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting
over 6 million people globally. Although there are symptomatic treatments that can increase …
over 6 million people globally. Although there are symptomatic treatments that can increase …
Automated accurate detection of depression using twin Pascal's triangles lattice pattern with EEG Signals
Electroencephalogram (EEG)-based major depressive disorder (MDD) machine learning
detection models can objectively differentiate MDD from healthy controls but are limited by …
detection models can objectively differentiate MDD from healthy controls but are limited by …
PatchResNet: multiple patch division–based deep feature fusion framework for brain tumor classification using MRI images
Modern computer vision algorithms are based on convolutional neural networks (CNNs),
and both end-to-end learning and transfer learning modes have been used with CNN for …
and both end-to-end learning and transfer learning modes have been used with CNN for …
Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach
Deep learning techniques have recently made considerable advances in the field of artificial
intelligence. These methodologies can assist psychologists in early diagnosis of mental …
intelligence. These methodologies can assist psychologists in early diagnosis of mental …
The emergence of AI-based wearable sensors for digital health technology: a review
Disease diagnosis and monitoring using conventional healthcare services is typically
expensive and has limited accuracy. Wearable health technology based on flexible …
expensive and has limited accuracy. Wearable health technology based on flexible …
[HTML][HTML] Towards using cough for respiratory disease diagnosis by leveraging Artificial Intelligence: A survey
Cough acoustics contain multitudes of vital information about pathomorphological
alterations in the respiratory system. Reliable and accurate detection of cough events by …
alterations in the respiratory system. Reliable and accurate detection of cough events by …
A comprehensive survey on the detection, classification, and challenges of neurological disorders
Simple Summary This study represents a resourceful review article that can deliver
resources on neurological diseases and their implemented classification algorithms to …
resources on neurological diseases and their implemented classification algorithms to …
Survey of machine learning techniques in the analysis of EEG signals for Parkinson's disease: A systematic review
AM Maitin, JP Romero Muñoz, ÁJ García-Tejedor - Applied Sciences, 2022 - mdpi.com
Background: Parkinson's disease (PD) affects 7–10 million people worldwide. Its diagnosis
is clinical and can be supported by image-based tests, which are expensive and not always …
is clinical and can be supported by image-based tests, which are expensive and not always …
An ideal ratiometric fluorescent probe provided by the surface modification of carbon dots for the determination of Pb2+
Herein, carbon dots (Cdots) with a single green emission peak and no response to metal
ions were converted to a high sensitive and selective ratiometric fluorescent probe for the …
ions were converted to a high sensitive and selective ratiometric fluorescent probe for the …