Machine learning algorithms for epilepsy detection based on published EEG databases: A systematic review

A Miltiadous, KD Tzimourta, N Giannakeas… - IEEE …, 2022 - ieeexplore.ieee.org
Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …

[HTML][HTML] Artificial Intelligence based accurately load forecasting system to forecast short and medium-term load demands

FM Butt, L Hussain, A Mahmood… - Mathematical Biosciences …, 2021 - aimspress.com
An efficient management and better scheduling by the power companies are of great
significance for accurate electrical load forecasting. There exists a high level of uncertainties …

Intelligence based accurate medium and long term load forecasting system

FM Butt, L Hussain, SHM Jafri… - Applied Artificial …, 2022 - Taylor & Francis
In this study, we aim to provide an efficient load prediction system projected for different local
feeders to predict the Medium-and Long-term Load Forecasting. This model improves future …

[PDF][PDF] Machine learning based congestive heart failure detection using feature importance ranking of multimodal features

L Hussain, W Aziz, IR Khan, MH Alkinani… - Math Biosci …, 2021 - pdfs.semanticscholar.org
In this study, we ranked the Multimodal Features extracted from Congestive Heart Failure
(CHF) and Normal Sinus Rhythm (NSR) subjects. We categorized the ranked features into 1 …

A feature-level degradation measurement method for composite health index construction and trend prediction modeling

W Jiang, Y Xu, Z Chen, N Zhang, X Xue, J Liu, J Zhou - Measurement, 2023 - Elsevier
Accurate measurement of degradation levels and evolution trend for mechanical equipment
has great significance to achieve the goal of condition-based maintenance (CBM) and …

Analyzing the dynamics of lung cancer imaging data using refined fuzzy entropy methods by extracting different features

L Hussain, W Aziz, AA Alshdadi, MSA Nadeem… - IEEE …, 2019 - ieeexplore.ieee.org
Lung cancer is the major cause of cancer-related deaths worldwide with poor survival due to
the poor diagnostic system at the advanced cancer stage. In the past, researchers …

An optimized gradient boosting model by genetic algorithm for forecasting crude oil production

EH Alkhammash - Energies, 2022 - mdpi.com
The forecasting of crude oil production is essential to economic plans and decision-making
in the oil and gas industry. Several techniques have been applied to forecast crude oil …

Load Forecasting of Electric Power Distribution System using Different Techniques: A Review

CK Mandara, VK Jadoun… - 2022 IEEE Students …, 2022 - ieeexplore.ieee.org
Today's complex civilization requires a steady and constant supply of electrical energy. It's
crucial because electrical power creation necessitates effective management. This is …

The choice of evaluation metrics in the prediction of epileptiform activity

N Gromov, A Lebedeva, I Kipelkin, O Elshina… - International Conference …, 2023 - Springer
In this study, we investigate the problem of prediction of epileptiform activity from EEG data
using a deep learning approach. We implement LSTM deep neural network and study how …

Enhanced Data Processing and Machine Learning Techniques for Energy Consumption Forecasting

J Shin, H Moon, T Sim, E Kim, S Lee - Electronics, 2024 - search.proquest.com
Energy consumption plays a significant role in global warming. In order to achieve carbon
neutrality and enhance energy efficiency through a stable energy supply, it is necessary to …