Diagnosis methods for COVID-19: a systematic review
R Maia, V Carvalho, B Faria, I Miranda, S Catarino… - Micromachines, 2022 - mdpi.com
At the end of 2019, the coronavirus appeared and spread extremely rapidly, causing millions
of infections and deaths worldwide, and becoming a global pandemic. For this reason, it …
of infections and deaths worldwide, and becoming a global pandemic. For this reason, it …
Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data
Abstract Coronavirus Disease 2019 (COVID-19) is extremely infectious and rapidly
spreading around the globe. As a result, rapid and precise identification of COVID-19 …
spreading around the globe. As a result, rapid and precise identification of COVID-19 …
[Retracted] Deep Learning‐Based Sentiment Analysis of COVID‐19 Vaccination Responses from Twitter Data
KN Alam, MS Khan, AR Dhruba… - … Methods in Medicine, 2021 - Wiley Online Library
The COVID‐19 pandemic has had a devastating effect on many people, creating severe
anxiety, fear, and complicated feelings or emotions. After the initiation of vaccinations …
anxiety, fear, and complicated feelings or emotions. After the initiation of vaccinations …
Early prediction of diabetes using an ensemble of machine learning models
Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of
significant complications, including cardiovascular disease, kidney failure, diabetic …
significant complications, including cardiovascular disease, kidney failure, diabetic …
[HTML][HTML] Comparison of multiclass classification techniques using dry bean dataset
Background The application of classsification methods through multivariate and machine
learning techniques has enormous significance in agricultural sector. It is vital to classify …
learning techniques has enormous significance in agricultural sector. It is vital to classify …
A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine
Since 2019, the COVID-19 pandemic has had an extremely high impact on all facets of the
society and will potentially have an everlasting impact for years to come. In response to this …
society and will potentially have an everlasting impact for years to come. In response to this …
Artificial Neural Network‐Based Deep Learning Model for COVID‐19 Patient Detection Using X‐Ray Chest Images
The world is experiencing an unprecedented crisis due to the coronavirus disease (COVID‐
19) outbreak that has affected nearly 216 countries and territories across the globe. Since …
19) outbreak that has affected nearly 216 countries and territories across the globe. Since …
XGB-RF: A hybrid machine learning approach for IoT intrusion detection
In the past few years, Internet of Things (IoT) devices have evolved faster and the use of
these devices is exceedingly increasing to make our daily activities easier than ever …
these devices is exceedingly increasing to make our daily activities easier than ever …
An improved machine-learning approach for COVID-19 prediction using Harris Hawks optimization and feature analysis using SHAP
A healthcare monitoring system needs the support of recent technologies such as artificial
intelligence (AI), machine learning (ML), and big data, especially during the COVID-19 …
intelligence (AI), machine learning (ML), and big data, especially during the COVID-19 …
[HTML][HTML] Imprecise bayesian optimization
Bayesian optimization (BO) with Gaussian processes (GPs) surrogate models is widely used
to optimize analytically unknown and expensive-to-evaluate functions. In this paper, we …
to optimize analytically unknown and expensive-to-evaluate functions. In this paper, we …