Breast cancer incidence has been rising steadily during the past few decades. It is the
second leading cause of death in women. If it is diagnosed early, there is a good possibility …

Alzheimer is a progressive disease and it is the most prevalent neurodegenerative disorder.
It is believed that the people with mild cognitive impairment are at high risk of developing …

The quality of operation of neural networks in solving application problems is determined by
the success of the stage of their training. The task of learning neural networks is a complex …

Recently, multistep-ahead prediction has attracted much attention in electric load forecasting
because it can deal with sudden changes in power consumption caused by various events …

The reliable control of wave energy devices highly relies on the forecasts of wave heights.
However, the dynamic characteristics and significant fluctuation of waves' historical data …

An approach to use Operational Intelligence with mathematical modeling and Machine
Learning to solve industrial technology projects problems are very crucial for today's IT …

As artificial intelligence systems gain traction, their trustworthiness becomes paramount to
harness their benefits and mitigate risks. This study underscores the pressing need for an …

Electroencephalogram (EEG) signals have been generally utilized for diagnostic systems.
Nowadays artificial intelligence-based systems have been proposed to classify EEG signals …

Background: The application of machine learning (ML) tools (MLTs) to support clinical trials
outputs in evidence-based health informatics can be an effective, useful, feasible, and …

The deep learning (DL) approaches in smart grid (SG) describes the possibility of shifting
the energy industry into a modern era of reliable and sustainable energy networks. This …