The rise of online platforms has transformed the discourse landscape, enabling users to create and share content actively, thereby shaping public perceptions and societal narratives. Understanding the dynamics of this discourse is essential for comprehending its socio-political implications. This review aims to provide a comprehensive overview of Critical Discourse Analysis (CDA) concerning online platforms, exploring how language is utilized across various digital contexts to influence identity formation and social inequalities. Methodologically, the review systematically searches electronic databases, including Google Scholar and ProQuest, using keywords related to CDA and online platforms. A total of 30 relevant studies are purpo

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

KE Sharquie, WS Al-Dori, IK Sharquie, AA Al–Nuaimy, Hospital, 2004 - Cited by 20

KE Sharquie, AA Noaimi, MS Al-Zoubaidi, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 8

KE Sharquie, AA Noaimi, S Al-Hashimy, IGF Al-Tereihi, The Iraqi Postgraduate Medical Journal, 2013 - Cited by 5

HR Al-Hamamy, KE Sharquie, AA Noaimi, WN Hussein, Our Dermatology Online, 2014 - Cited by 6

Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.