Early detection of student degree-level academic performance using educational data mining.

Higher educational institutes generate massive amounts of student data. This data needs to be explored in depth to better understand various facets of student learning behavior. The educational data mining approach has given provisions to extract useful and non-trivial knowledge from large collections of student data.

A Convolutional Neural Network Architecture for Segmentation of Lung Diseases Using Chest X-ray Images.

The segmentation of lungs from medical images is a critical step in the diagnosis and treatment of lung diseases. Deep learning techniques have shown great promise in automating this task, eliminating the need for manual annotation by radiologists. In this research, a convolution neural network architecture is proposed for lung segmentation using chest X-ray images.

Computing Drug-Drug Similarity from Patient-Centric Data.

In modern biology and medicine, drug-drug similarity is a major task with various applications in pharmaceutical drug development. Various direct and indirect sources of evidence obtained from drug-centric data such as side effects, drug interactions, biological targets, and chemical structures are used in the current methods to measure the level of drug-drug similarity. This paper proposes a computational method to measure drug-drug similarity using a novel source of evidence that is obtained from patient-centric data.

U-Net Model with Transfer Learning Model as a Backbone for Segmentation of Gastrointestinal Tract.

The human gastrointestinal (GI) tract is an important part of the body. According to World Health Organization (WHO) research, GI tract infections kill 1.8 million people each year.

Leveraging Tweets for Artificial Intelligence Driven Sentiment Analysis on the COVID-19 Pandemic.

The COVID-19 pandemic has been a disastrous event that has elevated several psychological issues such as depression given abrupt social changes and lack of employment. At the same time, social scientists and psychologists have gained significant interest in understanding the way people express emotions and sentiments at the time of pandemics. During the rise in COVID-19 cases with stricter lockdowns, people expressed their sentiments on social media.

Automatic Left Ventricle Segmentation from Short-Axis Cardiac MRI Images Based on Fully Convolutional Neural Network.

Background: Left ventricle (LV) segmentation using a cardiac magnetic resonance imaging (MRI) dataset is critical for evaluating global and regional cardiac functions and diagnosing cardiovascular diseases. LV clinical metrics such as LV volume, LV mass and ejection fraction (EF) are frequently extracted based on the LV segmentation from short-axis MRI images. Manual segmentation to assess such functions is tedious and time-consuming for medical experts to diagnose cardiac pathologies.

Secure Telemedicine System Design for COVID-19 Patients Treatment Using Service Oriented Architecture.

The coronavirus pandemic, also known as the COVID-19 pandemic, is an ongoing virus. It was first identified on December 2019 in Wuhan, China, and later spread to 192 countries. As of now, 251,266,207 people have been affected, and 5,070,244 deaths are reported.

Social Media Analytics for Pharmacovigilance of Antiepileptic Drugs.

Epilepsy is a common neurological disorder worldwide and antiepileptic drug (AED) therapy is the cornerstone of its treatment. It has a laudable aim of achieving seizure freedom with minimal, if any, adverse drug reactions (ADRs). Too often, AED treatment is a long-lasting journey, in which ADRs have a crucial role in its administration.

The burden of bites and stings management: Experience of an academic hospital in the Kingdom of Saudi Arabia.

Purpose: The main aim of this study is to estimate the economic burden and prevalence of bites and stings injuries in Saudi Arabia.

Methods: A retrospective, cross-sectional study was conducted at King Saud University Medical City (KSUMC) for all bites and stings cases presented to the Emergency Department (ED) between the period June 2015 and May 2019.

Results: A total of 1328 bites and stings cases were treated in the ED at KSUMC.

Pharmacist-led Medication Counseling for Patients Undergoing Hemodialysis: A Path to Better Adherence.

Objective: The primary objective was to assess the satisfaction of patients undergoing hemodialysis regarding counseling services provided by pharmacists. The secondary objectives were to compare the effect of years on dialysis and the presence of comorbidities on patient satisfaction.

Methods: A total of 138 patients were included in the study, and all demographic and clinical variables were retrieved from the dialysis unit records of King Abdulaziz Medical City over a period of 4 months from July to October 2015.

UPLC/MS-MS assay development for estimation of mozavaptan in plasma and its pharmacokinetic study in rats.

Aim: Mozavaptan is a nonpeptide vasopressin receptor antagonist approved for the treatment of ectopic antidiuretic hormone secretion syndrome.

Methods & Results: A simple, rapid and fully validated UPLC/MS-MS method was developed for the quantitation of mozavaptan in rat plasma. The chromatographic separation was conducted on an Acquity UPLC BEH™ C column with an optimum mobile phase of 10 mM ammonium acetate buffer and 0.

Pharmacy education in Saudi Arabia: A vision of the future.

Pharmacy education in developing countries faces many challenges. An assessment of the challenges and opportunities for the future of pharmacy education in Saudi Arabia has not been conducted. The purpose of the study was to ascertain the views and opinions of pharmacy education stakeholders regarding the current issues challenging pharmacy education, and to discuss the future of pharmacy education in Saudi Arabia.