Chaotic time series prediction, a challenging research topic in dynamic system modeling,
has drawn great attention from researchers around the world. In recent years extensive …

Deep learning (DL) is becoming a fast-growing field in the medical domain and it helps in
the timely detection of any infectious disease (IDs) and is essential to the management of …

Research background: Deep and machine learning-based algorithms can assist in COVID-
19 image-based medical diagnosis and symptom tracing, optimize intensive care unit …

Traditional time series prediction methods have shown their outstanding capabilities in time
series prediction. However, due to essential differences in volatility characteristics among …

This paper shows that time series forecasting Transformer (TSFT) suffers from severe over-
fitting problem caused by improper initialization method of unknown decoder inputs …

The COVID-19 pandemic has affected many aspects of human life around the world, due to
its tremendous outcomes on public health and socio-economic activities. Policy makers …

Electroencephalography (EEG) serves as a diagnostic technique for measuring brain waves
and brain activity. Despite its precision in capturing brain electrical activity, certain factors …

Using medical science alongside time series data analysis can be given a strong tool to
develop efficient decision support systems in Corona pandemic. In this regard, many hybrid …

Background Accurate incidence prediction of sexually transmitted diseases (STDs) is critical
for early prevention and better government strategic planning. In this paper, four different …

Alzheimer's disease (AD) is the leading cause of dementia globally, with a growing morbidity
burden that may exceed diagnosis and management capabilities. The situation worsens …