Human activity recognition using MotionNode sensors is getting prominence effect in our
daily life logs. Providing accurate information on human's activities and behaviors is one of …

In the last decade, the implementation of machine learning algorithms in the analysis of
voice disorder is paramount in order to provide a non-invasive voice pathology detection by …

The utilisation of ML (Machine Learning) techniques in the detection of the VP (Voice
Pathology) has recently gained a lot of consideration. However, these efforts still have …

Objectives Advances in artificial intelligence (AI) technology have increased the feasibility of
classifying voice disorders using voice recordings as a screening tool. This work develops …

Simple Summary A total laryngectomy involves the full and permanent separation of the
upper and lower airways, resulting in the loss of voice and inability to interact vocally. To …

Non-invasive acoustic analyses of voice disorders have been at the forefront of current
biomedical research. Usual strategies, essentially based on machine learning (ML) …

Automatic voice pathology detection using non-invasive techniques that utilize patients'
speech and electroglottograph (EGG) signals play a vital role in diagnosis and early medical …

The purpose of this research was to develop an artificial intelligence-based method for
evaluating substitution voicing (SV) and speech following laryngeal oncosurgery …

The use of a back-propagation artificial neural network (ANN) to systematize the reliability of
a Deep Vein Thrombosis (DVT) diagnostic by using Wells' criteria is introduced herein. In …

Simple Summary This paper introduces a new method for cleaning impaired speech by
combining Pareto-optimized deep learning with Non-negative Matrix Factorization (NMF) …