OBJECTIVE: To develop and validate a deep neural network (DNN) model for diagnosing Parkinson's Disease (PD) using handwritten spiral and wave images, and to compare its performance with various machine learning (ML) and deep learning (DL) models.
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2025
Artificial neural networks are receiving increasing attention from researchers. However, with the advent of big data era, artificial neural networks are limited by the Von Neumann architecture, making it difficult to make new breakthroughs in hardwar...
International journal of biological macromolecules
Jan 13, 2025
Wearable devices that incorporate flexible pressure sensors have shown great potential for human-machine interaction, speech recognition, health monitoring, and handwriting recognition. However, achieving high sensitivity, durability, wide detection ...
BMC medical informatics and decision making
Sep 27, 2024
Parkinson's disease (PD) is classified as a neurological, progressive illness brought on by cell death in the posterior midbrain. Early PD detection will assist doctors in reducing the disease's consequences. A collection of skilled models that may b...
With over 55 million people globally affected by dementia and nearly 10 million new cases reported annually, Alzheimer's disease is a prevalent and challenging neurodegenerative disorder. Despite significant advancements in machine learning technique...
Accurate air-writing recognition is pivotal for advancing state-of-the-art text recognizers, encryption tools, and biometric technologies. However, most existing air-writing recognition systems rely on image-based sensors to track hand and finger mot...
The combination of wearable sensors with machine learning enables intelligent perception in human-machine interaction and healthcare, but achieving high sensitivity and a wide working range in flexible strain sensors for signal acquisition and accura...
Journal of the World federation of orthodontists
Sep 3, 2024
BACKGROUND: The purpose of this study was to compare the success of various convolutional neural network (CNN) models trained with handwriting samples in predicting patient cooperation.
Conductive hydrogels are widely used in flexible sensors owing to their adjustable structure, good conductivity, and flexibility. The performance of excellent mechanical properties, high sensitivity, and elastic modulus compatible with human tissues ...
In an era marked by escalating concerns about digital security, biometric identification methods have gained paramount importance. Despite the increasing adoption of biometric techniques, keystroke dynamics analysis remains a less explored yet promis...
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