Abstract Time Series Classification (TSC) is an important and challenging problem in data
mining. With the increase of time series data availability, hundreds of TSC algorithms have …

Analysis of big data by machine learning offers considerable advantages for assimilation
and evaluation of large amounts of complex health-care data. However, to effectively use …

Abstract The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of
China in December 2019, spread rapidly around the world and became a pandemic. It has …

This article presents a new deep learning approach for cardiac arrhythmia (17 classes)
detection based on long-duration electrocardiography (ECG) signal analysis …

Abstract Purpose of Review Artificial intelligence (AI) technology holds both great promise to
transform mental healthcare and potential pitfalls. This article provides an overview of AI and …

Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …

Mental health is a basic need for a sustainable and develo** society. The prevalence and
financial burden of mental illness have increased globally, and especially in response to …

Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …

Objectives The availability of large and varied Electroencephalogram (EEG) datasets,
rapidly advances and inventions in deep learning techniques, and highly powerful and …

A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …