Epilepsy, one of the most severe neurological diseases, is characterized by abrupt recurrent
seizures. Despite great progress in the development of antiseizure drugs (ASDs) based on …

Emotion recognition using brain signals has the potential to change the way we identify and
treat some health conditions. Difficulties and limitations may arise in general emotion …

Neonatology has experienced a significant reduction in mortality rates of the preterm
population and critically ill infants over the last few decades. Now, the emphasis is directed …

Purpose Build machine learning models for predicting pressure ulcer nursing adverse event,
and find an optimal model that predicts the occurrence of pressure ulcer accurately. Patients …

Background Most trials in critical care have been neutral, in part because between-patient
heterogeneity means not all patients respond identically to the same treatment. The …

Despite the relatively small number of items in the GAD-7, fewer items are increasingly
sought to shorten testing time in large-scale mental health screenings. As a result, short …

Introduction Current electroencephalography (EEG) practice relies on interpretation by
expert neurologists, which introduces diagnostic and therapeutic delays that can impact …

Great strides have been made recently in documenting that machine-learning programs can
predict seizure occurrence in people who have epilepsy. Along with this progress have …

The neurological ICU (neuro ICU) often suffers from significant limitations due to scarce
resource availability for their neurocritical care patients. Neuro ICU patients require frequent …

Critical care long-term continuous electroencephalogram (cEEG) monitoring has expanded
dramatically in the last several decades spurned by technological advances in EEG …