The Role of Artificial Intelligence in Medical Imaging: From Diagnosis to Ethical Frontiers

Artificial intelligence (AI) has made a significant difference in radiology, particularly in machine learning and deep learning approaches, for improving tasks such as image processing and X-ray detection. It relies on optimizing the operations and predictions in analytics, computer diagnostics, and image segmentation. Clinical procedures rely on personalized medication and diagnostic techniques. The challenges AI encounters in radiography include the ‘black box’ issue, accuracy of data, technological and infrastructural complexity, ethical issues such as patient privacy and data security, overreliance on AI, and bias. This article determines the various aspects involved in the use of AI in medical diagnosis (radiological), summarizes the performance of AI in detecting and diagnosing diseases from different radiology procedures, and highlights the potential challenges and ethical issues. AI has a significant impact on radiology and highlights its huge influence on the specialty; it can be used to detect certain pathological conditions, such as cancer, Mets, liver fibrosis, and thyroid disorder. Furthermore, AI aids in assessing the progression of diseases, evaluating therapy responses, and predicting patient outcomes. In cancer treatment, AI can determine tumor size and growth over time, offering essential data for treatment planning. Artificial intelligence in radiology provides significant potential for enhancing diagnostic precision, efficiency, and workflow. However, its incorporation into clinical practice faces several challenges.