SEL-COVIDNET: An intelligent application for the diagnosis of COVID-19 from chest X-rays and CT-scans.

COVID-19 detection from medical imaging is a difficult challenge that has piqued the interest of experts worldwide. Chest X-rays and computed tomography (CT) scanning are the essential imaging modalities for diagnosing COVID-19. All researchers focus their efforts on developing viable methods and rapid treatment procedures for this pandemic.

Awareness and Knowledge of Pharmacists toward Biosimilar Medicines: A Survey in Jordan.

Aims: Pharmacists in all clinical settings are recognized drug experts and integral educators of biosimilar medicines. Therefore, the objective of this study was to assess pharmacists' knowledge, predictors of knowledge, and views toward biosimilar medicines in Jordan.

Methods: A cross-sectional study was conducted in Jordan during October-December 2020.

Evaluation of E-learning Experience in the Light of the Covid-19 in Higher Education.

Covid-19 has been stated as a worldwide outbreak of pandemic disease and crisis. The Covid-19 pandemic has dramatically affected the teaching and learning experience at universities and schools. In response, governments and higher education institutions around the world put significant efforts to ensure that students continue to obtain the best possible level of education and learning outcomes.

About anxiety levels and anti-anxiety drugs among quarantined undergraduate Jordanian students during COVID-19 pandemic.

Objective: This study was conducted to study the anxiety scores among undergraduate university students in Jordan during COVID-19 pandemic and to assess the relationship between quarantine and shifting to distance learning resulted from the governmental strict isolation measures and severity of anxiety among students.

Methods: A cross-sectional design was conducted to meet the study objectives. A convenience sample of 736 undergraduate university students in Jordan was recruited, and anxiety was assessed using the Hamilton Anxiety Scale.

A Transfer Learning Approach for Early Diagnosis of Alzheimer's Disease on MRI Images.

Mild cognitive impairment (MCI) detection using magnetic resonance image (MRI), plays a crucial role in the treatment of dementia disease at an early stage. Deep learning architecture produces impressive results in such research. Algorithms require a large number of annotated datasets for training the model.