A machine learning-based model for epidemic forecasting and faster drug discovery

KD Stergiou, GM Minopoulos, VA Memos… - Applied Sciences, 2022 - mdpi.com
Today, healthcare system models should have high accuracy and sensitivity so that patients
do not have a misdiagnosis. For this reason, sufficient knowledge of the area is required …

[HTML][HTML] Minimizing liability of the COVID-19 pandemic on construction contracts—A structural equation model for risk mitigation of force majeure impacts

AA Chadee, S Gallage, HH Martin, U Rathnayake… - Buildings, 2023 - mdpi.com
A pandemic is a force majeure event, and contracting parties can invoke conditions under
force majeure to minimize liability for unforeseen, uncontrollable, and unavoidable …

AraXLNet: pre-trained language model for sentiment analysis of Arabic

A Alduailej, A Alothaim - Journal of Big Data, 2022 - Springer
The Arabic language is a complex language with little resources; therefore, its limitations
create a challenge to produce accurate text classification tasks such as sentiment analysis …

PulmoNet: a novel deep learning based pulmonary diseases detection model

ART Abdulahi, RO Ogundokun, AR Adenike… - BMC Medical …, 2024 - Springer
Pulmonary diseases are various pathological conditions that affect respiratory tissues and
organs, making the exchange of gas challenging for animals inhaling and exhaling. It varies …

The work-life balancing act: A study on the mandatory work from home due to COVID-19 on the IT and non-IT industry sectors

D Pathak - International Journal of Human Capital and Information …, 2021 - igi-global.com
The study investigated the impact of mandatory work from home due COVID-19 on personal
and professional lives of people with different demographics. Statistical analysis of an online …

Hybrid optimal feature selection-based iterative deep convolution learning for COVID-19 classification system

PSK Patra, B Tripathy - Computers in Biology and Medicine, 2024 - Elsevier
The COVID-19 pandemic has necessitated the development of innovative and efficient
methods for early detection and diagnosis. Integrating Internet of Things (IoT) devices and …

[PDF][PDF] Comparative Analysis of COVID-19 Detection Methods Based on Neural Network.

I Hilali-Jaghdam, AA Elhag, AB Ishak… - … Materials & Continua, 2023 - cdn.techscience.cn
In 2019, the novel coronavirus disease 2019 (COVID-19) ravaged the world. As of July
2021, there are about 192 million infected people worldwide and 4.1365 million deaths. At …

Evaluating the performance of ID3 method to analyze and predict students' performance in online platforms

M Al Karim, MS Tahsin, MU Ahmed… - 2022 International …, 2022 - ieeexplore.ieee.org
The primary goal of this work was to establish the influence of the epidemic on education,
especially the impact of online platforms on students' overall performance. To improve …

Predicting the outcomes of football matches using machine learning approach

U Haruna, JZ Maitama, M Mohammed… - … Conference on Informatics …, 2021 - Springer
Predicting outcomes of football matches is among the rapid growing area of research due to
the interest of large number of people, and the stochastic nature of the results. Many …

Fault detection and separation of hybrid electric vehicles based on kernel orthogonal subspace analysis

Y Wang, S Deprizon, C Peng… - Journal of Applied …, 2023 - aseestant.ceon.rs
Driving quality and vehicles safety of hybrid electric vehicles (HEVs) are two hot-topic issues
in automobile technology. Nowadays, research focuses to more intelligent and convenient …