Abstract Integrating Machine Learning (ML) in medicine has unlocked many opportunities to
harness complex medical data, enhancing patient outcomes and advancing the field …

The healthcare industry is rapidly automating, in large part because of the Internet of Things
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …

Electroencephalogram (EEG) is one of the main diagnostic tests for epilepsy. The detection
of epileptic activity is usually performed by a human expert and is based on finding specific …

As one of the most common cancers globally, the incidence of skin cancer has been rising.
Dermoscopy-based classification has become the most effective method for the diagnosis of …

Epilepsy affects around 1% of the population worldwide. Anti-epileptic drugs are an
excellent option for controlling seizure occurrence but do not work for around one-third of …

Epileptic seizure detection and prediction are significantly sought-after research currently
because robust algorithms are available. Machine learning and deep learning have allowed …

Ever since the outbreak of COVID-19, the entire world is grappling with panic over its rapid
spread. Consequently, it is of utmost importance to detect its presence. Timely diagnostic …

Epileptic EEG signal recognition is an important method for epilepsy detection. In essence,
epileptic EEG signal recognition is a typical imbalanced classification task. However …

Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …

Attention deficit hyperactivity disorder (ADHD) is a neurological disorder that affects an
individual's behavior. The rising cases of ADHD among children and adolescents worldwide …