Published Paper Details:

This paper offers an exploratory analysis on the application of artificial intelligence (AI) in medical imaging during the diagnosis process with an aim of increasing both accuracy and efficiency. The constantly growing complexity of medical imaging data coupled with the huge burden of doctors to reach appropriate diagnosis promptly and accurately, has led AI into the domain of assisting medical practitioners interpreting their studies [1]. Through a comprehensive analysis of existing literature and research, this study considers how AI improves diagnostic precision, cuts down interpretation time, and allows early diagnosis of diseases in different medical imaging modalities namely MRI, CT scans, X-rays and ultrasound. This research adds to the knowledge of how AI can transform the imaging practices and healing process through the emerging of opportunities and constraints related to the implementation of AI-assisted medical imaging [1]. Moreover, this paper discusses AI's role in imaging for the providers, patients, and healthcare system together, and how it has revolutionized drug recognition and patient care. Furthermore, the implementation of AI-powered medical imaging devices in clinical workshells involves the account of numerous issues such as compliance with rules and regulations, compatibility with the existing healthcare system and user opinion. Pilot studies and implementation trials conducted in actual clinical settings realize AI algorithms contribute to the process of care workflow design, resources involved and patient outcomes assessment.