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

Epileptic seizure is one of the most chronic neurological diseases that instantaneously
disrupts the lifestyle of affected individuals. Toward develo** novel and efficient …

Correctly interpreting an Electroencephalography (EEG) signal with high accuracy is a
tedious and time-consuming task that may take several years of manual training due to its …

The extensive growth of data in the health domain has increased the utility of Deep Learning
in health. Deep learning is a highly advanced successor of artificial neural networks, having …

Fluorescent nanomaterials such as carbon quantum dots (CQDs) have been widely utilized
as optical nanosensors for the detection and imaging of chemical or biological species with …

Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …

Deep learning has achieved excellent performance in a wide range of domains, especially
in speech recognition and computer vision. Relatively less work has been done for …

Heart disease causes major death across the entire globe. Hence, heart disease prediction
is a vital part of medical data analysis. Recently, various data mining and machine learning …

Abstract Purpose Parkinson's Disease comes on top among neurodegenerative diseases
affecting 10 million worldwide. To detect Parkinson's Disease in a prior state, gait analysis is …

The number of devices connected to the Internet is increasing day by day. This increase
causes cyber-attacks to be larger and more complex. It is important to sdetect the anomalies …