[HTML][HTML] Automatic and early detection of Parkinson's disease by analyzing acoustic signals using classification algorithms based on recursive feature elimination …

KM Alalayah, EM Senan, HF Atlam, IA Ahmed… - Diagnostics, 2023 - mdpi.com
Parkinson's disease (PD) is a neurodegenerative condition generated by the dysfunction of
brain cells and their 60–80% inability to produce dopamine, an organic chemical …

Sentiment analysis of image with text caption using deep learning techniques

PK Chaubey, TK Arora, KB Raj… - Computational …, 2022 - Wiley Online Library
People are actively expressing their views and opinions via the use of visual pictures and
text captions on social media platforms, rather than just publishing them in plain text as a …

A modified binary version of aphid–ant mutualism for feature selection: A COVID-19 case study

N Eslami, S Yazdani, M Mirzaei… - Journal of …, 2023 - academic.oup.com
The speedy development of intelligent technologies and gadgets has led to a drastic
increment of dimensions within the datasets in recent years. Dimension reduction …

Energy efficient and secure information dissemination in heterogeneous wireless sensor networks using machine learning techniques

D Dudeja, SY Hera, NV Doohan… - Wireless …, 2022 - Wiley Online Library
The extensive use of sensor technology in every sphere of life, along with the continuous
digitization of society, makes it realistic to anticipate that the planet will soon be patched with …

Improved UNet deep learning model for automatic detection of lung cancer nodules

V Kumar, BR Altahan, T Rasheed… - Computational …, 2023 - Wiley Online Library
Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent
kind of cancer. When cells from the lungs spread to other tissues and organs, this is referred …

A Cloud‐Based Machine Learning Approach to Reduce Noise in ECG Arrhythmias for Smart Healthcare Services

P Jain, WF Alsanie, DO Gago… - Computational …, 2022 - Wiley Online Library
ECG (electrocardiogram) identifies and traces targets and is commonly employed in cardiac
disease detection. It is necessary for monitoring precise target trajectories. Estimations of …

An Effective Deep Learning Model for Health Monitoring and Detection of COVID‐19 Infected Patients: An End‐to‐End Solution

VG Biradar, MA Alqahtani, HC Nagaraj… - Computational …, 2022 - Wiley Online Library
The COVID‐19 infection is the greatest danger to humankind right now because of the
devastation it causes to the lives of its victims. It is important that infected people be tested in …

Analysis of Smart Lung Tumour Detector and Stage Classifier Using Deep Learning Techniques with Internet of Things

S Joshi, SV Pandit, PK Shukla… - Computational …, 2022 - Wiley Online Library
The use of artificial intelligence (AI) and the Internet of Things (IoT), which is a developing
technology in medical applications that assists physicians in making more informed …

Effective EEG Feature Selection for Interpretable MDD (Major Depressive Disorder) Classification

V Mrazek, S Jawed, M Arif, AS Malik - Proceedings of the Genetic and …, 2023 - dl.acm.org
In this paper, we propose an interpretable electroencephalogram (EEG)-based solution for
the diagnostics of major depressive disorder (MDD). The acquisition of EEG experimental …

Real-Time Sentiment Analysis and Spam Detection Using Machine Learning and Deep Learning

MM Abdulhasan, H Alchilibi, MA Mohammed… - … Conference on Data …, 2023 - Springer
In our environment, constant information exposure is required and done in a certain way.
Twitter, Facebook, and Quora struggle to handle spam accounts. Automated software …