Anomaly detection has recently been applied to various areas, and several techniques
based on deep learning have been proposed for the analysis of multivariate time series. In …

Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology
have brought on substantial strides in predicting and identifying health emergencies …

State space models (SSMs) have demonstrated state-of-the-art sequence modeling
performance in some modalities, but underperform attention in language modeling …

Presently, COVID-19 has posed a serious threat to researchers, scientists, health
professionals, and administrations around the globe from its detection to its treatment. The …

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

Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …

Automated seizure detection and classification from electroencephalography (EEG) can
greatly improve seizure diagnosis and treatment. However, several modeling challenges …

Electroencephalogram (EEG) datasets from epilepsy patients have been used to develop
seizure detection and prediction algorithms using machine learning (ML) techniques with …

Water pollution is one of the serious threats in the society. More than 8 million tons of plastic
are dumped in the oceans each year. In addition to that beaches are littered by tourists and …

Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy
have increased exponentially over the past decade. Integration of AI into epilepsy …