Artificial Intelligence in Radiology: A Narrative Review
AI in Radiology
Keywords:
Artificial Intelligence, Machine learning, Diagnostic imaging, Patient care, Convolutional neural networkAbstract
Radiology undoubtedly plays a crucial role as the backbone of diagnostic imaging. It is one of the most sought-after specialties owing to a work-life balance and minimal patient interaction. The advent of Artificial Intelligence has undoubtedly proven to be a boon with online prescriptions, telemedicine, and advanced technology, revolutionizing image-based diagnostic techniques. It is bound to bring tremendous changes in the way one predicts the course of a disease, especially those relying on pattern recognition. The practice of radiology is set to witness a seismic shift in the coming years with the increasing application of machine learning and deep learning. It is high time to embrace these changes and remain up to date with recent developments, as virtual medical assistants powered by AI can give doctors the much-needed gift of time while improving the precision in diagnosis and management. This article summarizes the past foundations, present practice, and future opportunities of AI in radiology and the concepts essential to understand this integration. It also highlights the fact that careful implementation can ensure equity and efficiency in patient management.
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Copyright (c) 2026 Dr Geeta Chand Acharya, Dr Sai Chandan Das, Dr Brojesh Rishi Mukherjee , Dr. Chetan Chowdhary , Dr Gitom Baruah , Prof (Dr) Alpana Mishra
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