[HTML][HTML] Machine learning approaches in COVID-19 diagnosis, mortality, and severity risk prediction: A review

N Alballa, I Al-Turaiki - Informatics in medicine unlocked, 2021 - Elsevier
The existence of widespread COVID-19 infections has prompted worldwide efforts to control
and manage the virus, and hopefully curb it completely. One important line of research is the …

Potential applications and performance of machine learning techniques and algorithms in clinical practice: a systematic review

EM Nwanosike, BR Conway, HA Merchant… - International journal of …, 2022 - Elsevier
Purpose The advent of clinically adapted machine learning algorithms can solve numerous
problems ranging from disease diagnosis and prognosis to therapy recommendations. This …

[HTML][HTML] Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests

F Cabitza, A Campagner, D Ferrari… - Clinical Chemistry and …, 2021 - degruyter.com
Objectives The rRT-PCR test, the current gold standard for the detection of coronavirus
disease (COVID-19), presents with known shortcomings, such as long turnaround time …

[HTML][HTML] Time series prediction of COVID-19 transmission in America using LSTM and XGBoost algorithms

J Luo, Z Zhang, Y Fu, F Rao - Results in Physics, 2021 - Elsevier
In this paper, we establish daily confirmed infected cases prediction models for the time
series data of America by applying both the long short-term memory (LSTM) and extreme …

[HTML][HTML] Automatic COVID-19 prediction using explainable machine learning techniques

S Solayman, SA Aumi, CS Mery, M Mubassir… - International Journal of …, 2023 - Elsevier
The coronavirus is considered this century's most disruptive catastrophe and global concern.
This disease has prompted extreme social, psychological and economic impacts affecting …

[HTML][HTML] Explaining machine learning based diagnosis of COVID-19 from routine blood tests with decision trees and criteria graphs

MA Alves, GZ Castro, BAS Oliveira, LA Ferreira… - Computers in Biology …, 2021 - Elsevier
The sudden outbreak of coronavirus disease 2019 (COVID-19) revealed the need for fast
and reliable automatic tools to help health teams. This paper aims to present …

Accurate detection of Covid-19 patients based on Feature Correlated Naïve Bayes (FCNB) classification strategy

NA Mansour, AI Saleh, M Badawy, HA Ali - Journal of ambient intelligence …, 2022 - Springer
The outbreak of Coronavirus (COVID-19) has spread between people around the world at a
rapid rate so that the number of infected people and deaths is increasing quickly every day …

[HTML][HTML] Ensemble learning model for diagnosing COVID-19 from routine blood tests

M AlJame, I Ahmad, A Imtiaz, A Mohammed - Informatics in Medicine …, 2020 - Elsevier
Background and objectives The pandemic of novel coronavirus disease 2019 (COVID-19)
has severely impacted human society with a massive death toll worldwide. There is an …

Machine learning sensors for diagnosis of COVID-19 disease using routine blood values for internet of things application

A Velichko, MT Huyut, M Belyaev, Y Izotov, D Korzun - Sensors, 2022 - mdpi.com
Healthcare digitalization requires effective applications of human sensors, when various
parameters of the human body are instantly monitored in everyday life due to the Internet of …

Clinical and laboratory approach to diagnose COVID-19 using machine learning

K Chadaga, C Chakraborty, S Prabhu… - Interdisciplinary …, 2022 - Springer
Abstract Coronavirus 2 (SARS-CoV-2), often known by the name COVID-19, is a type of
acute respiratory syndrome that has had a significant influence on both economy and health …