Predicting vitamin D deficiency using optimized random forest classifier.

Background: Vitamin D can be acquired from various dietary sources, but exposure to sunlight's ultraviolet rays can convert a natural compound called ergosterol present in the skin into vitamin D.

Aim: The current study aimed to investigate vital parameters and use an optimized random forest (OptRF) classifier to understand better and predict the effect of environmental and nutritional factors of Vitamin D deficiency.

Methods: A predictive, cross-sectional, and correlational design was utilized in a study involving 350 male and female Tabuk citizens in Saudi Arabia.

Digitalization of learning in Saudi Arabia during the COVID-19 outbreak: A survey.

Following the outbreak of the novel coronavirus (COVID-19) in China in late December 2019, more than 217 countries became almost immediately infected in the resulting pandemic. Consequently, many of them decided to close their educational institutions as a way of preventing the spread of this virus. For many of them, though, the closure made them unable to deliver learning materials to students owing to their inability to provide the right technology for the purpose.

Internship training in computer science: Exploring student satisfaction levels.

The requirement of employability in the job market prompted universities to conduct internship training as part of their study plans. There is a need to train students on important academic and professional skills related to the workplace with an IT component. This article describes a statistical study that measures satisfaction levels among students in the faculty of Information Technology and Computer Science in Jordan.