The worldwide COVID-19 pandemic has resulted in millions of fatalities and significantly altered the lives of many individuals. The prompt and effective Finding COVID-19 cases is essential to reducing the virus's spread. SARS-CoV-2 virus; however, this task presents considerable challenges for the healthcare sector. The demonstrated success of artificial intelligence (AI) across various scientific fields has inspired researchers to investigate its potential in addressing this urgent issue. AI methodologies, when combined with medical imaging techniques such as X-rays, computed tomography (CT), and ultrasound (US), have shown considerable promise in facilitating early and precise diagnoses of COVID-19. This document offers a comprehensive review of advanced AI techniques utilized in these imaging modalities for the detection of COVID-19. We classify these methodologies, underscore their effectiveness, and examine their contributions to pandemic management. Furthermore, the paper addresses the obstacles associated with the deployment of AI-driven systems, including limitations in data availability, ethical dilemmas, and technical challenges. It also considers future directions for AI-enhanced diagnostic systems, high lighting their potential to strengthen health care resilience in the face of pandemics. Through a thorough analysis of current research, this review seeks to provide meaningful insights into the role of AI in disease detection and its transformative influence on the healthcare industry during global health crises.