Background Artificial intelligence (AI) has served humanity in many applications since its
inception. Currently, it dominates the imaging field—in particular, image classification. The …

The first few months of 2020 have profoundly changed the way we live our lives and carry
out our daily activities. Although the widespread use of futuristic robotaxis and self-driving …

Anomaly detection of multivariate time series data has drawn extensive research attention
recently, as it can be widely applied into various different domains, such as Prognostics …

The COVID-19 epidemic has caused more than 6.4 million deaths to date and has become a
hot topic of interest in different disciplines. According to bibliometric analysis, more than …

During pandemic periods, there is an intense flow of patients to hospitals. Depending on the
disease, many patients may require hospitalization. In some cases, these patients must be …

In this study, we utilized unsupervised machine learning techniques to examine the
relationship between different symptoms in cases who died of COVID-19 and cases who …

Coronavirus is an endangered disease to kills more than millions of people, but it has also
put tremendous pressure on the whole medical system. The initial stage of identification of …

The COVID-19 pandemic has resulted in more than 440 million confirmed cases globally
and almost 6 million reported deaths as of March 2022. Consequently, the world …

Anomaly detection and explanation in big volumes of real-world medical data, such as those
pertaining to COVID-19, pose some challenges. First, we are dealing with time-series data …

We propose an automatic COVID1-19 diagnosis framework from lung CT-scan slice images
using double BERT feature extraction. In the first BERT feature extraction, A 3D-CNN is first …