Pneumonia detection in chest X-ray images using an ensemble of deep learning models
Pneumonia is a respiratory infection caused by bacteria or viruses; it affects many
individuals, especially in developing and underdeveloped nations, where high levels of …
individuals, especially in developing and underdeveloped nations, where high levels of …
The recent technologies to curb the second-wave of COVID-19 pandemic
Different epidemics, specially Coronavirus, have caused critical misfortunes in various fields
like monetary deprivation, survival conditions, thus diminishing the overall individual …
like monetary deprivation, survival conditions, thus diminishing the overall individual …
A comparative performance analysis of data resampling methods on imbalance medical data
Medical datasets are usually imbalanced, where negative cases severely outnumber
positive cases. Therefore, it is essential to deal with this data skew problem when training …
positive cases. Therefore, it is essential to deal with this data skew problem when training …
COVID-19 case recognition from chest CT images by deep learning, entropy-controlled firefly optimization, and parallel feature fusion
In healthcare, a multitude of data is collected from medical sensors and devices, such as X-
ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that …
ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that …
An overview of healthcare data analytics with applications to the COVID-19 pandemic
In the era of big data, standard analysis tools may be inadequate for making inference and
there is a growing need for more efficient and innovative ways to collect, process, analyze …
there is a growing need for more efficient and innovative ways to collect, process, analyze …
ANC: Attention network for COVID-19 explainable diagnosis based on convolutional block attention module
Y Zhang, X Zhang, W Zhu - Computer Modeling in Engineering …, 2021 - ingentaconnect.com
Aim: To diagnose COVID-19 more efficiently and more correctly, this study proposed a novel
attention network for COVID-19 (ANC). Methods: Two datasets were used in this study. An …
attention network for COVID-19 (ANC). Methods: Two datasets were used in this study. An …
Forecasting the monkeypox outbreak using ARIMA, prophet, NeuralProphet, and LSTM models in the United States
Since May 2022, over 64,000 Monkeypox cases have been confirmed globally up until
September 2022. The United States leads the world in cases, with over 25,000 cases …
September 2022. The United States leads the world in cases, with over 25,000 cases …
[Retracted] A Rapid Artificial Intelligence‐Based Computer‐Aided Diagnosis System for COVID‐19 Classification from CT Images
The excessive number of COVID‐19 cases reported worldwide so far, supplemented by a
high rate of false alarms in its diagnosis using the conventional polymerase chain reaction …
high rate of false alarms in its diagnosis using the conventional polymerase chain reaction …
A dual-stage attention-based Bi-LSTM network for multivariate time series prediction
In the context of the big data era, time series data present the characteristics of high
dimensionality and nonlinearity, which bring great challenges to the prediction of …
dimensionality and nonlinearity, which bring great challenges to the prediction of …
[PDF][PDF] Pseudo zernike moment and deep stacked sparse autoencoder for COVID-19 diagnosis
(Aim) COVID-19 is an ongoing infectious disease. It has caused more than 107.45 m
confirmed cases and 2.35 m deaths till 11/Feb/2021. Traditional computer vision methods …
confirmed cases and 2.35 m deaths till 11/Feb/2021. Traditional computer vision methods …