AICII 2026

AI Augmented Radiology in Resource Constrained Settings: Addressing India’s Imaging Inequality

Shruti
Chandigarh Group of College, Mohali, India

Conference Information

Conference 1st AARAI International Conference on Interdisciplinary Innovation
Acronym AICII 2026
Conference Date 26/09/2026
Mode Virtual
Location Online

Abstract

Access to timely and reliable diagnostic imaging remains an important challenge in many parts of India. Although radiology has become central to modern healthcare, access to imaging equipment, trained radiologists and specialist interpretation is not evenly distributed. The problem is particularly visible in rural and underserved communities, where patients may have to travel long distances or wait for specialist services before receiving a diagnosis. At the same time, artificial intelligence is rapidly changing the way medical images are acquired, interpreted and reported. This creates an important question for resource constrained healthcare settings: can artificial intelligence help extend the reach of radiology without compromising the role of clinical expertise?

This paper examines the potential of AI augmented radiology as a means of addressing imaging inequality in India. Drawing on existing literature on artificial intelligence, diagnostic imaging, tele radiology and healthcare access, the paper considers how AI may support image interpretation, case prioritisation, reporting and clinical decision making in settings where radiological expertise is limited. It also examines the challenges that may accompany its adoption, including cost, infrastructure, data quality, algorithmic bias, patient privacy, professional accountability and the need for appropriate human oversight.

The paper argues that the value of AI in resource constrained settings should not be measured simply by its technological sophistication or diagnostic accuracy. Its greater significance may lie in whether it can help make quality radiological expertise more accessible to populations that have historically experienced limited access to specialist care. The paper proposes an equitable approach to AI augmented radiology in which technology complements rather than replaces healthcare professionals and is introduced alongside appropriate infrastructure, validation, ethical safeguards and health system support. Such an approach could allow India to use emerging imaging technologies not only to improve diagnostic efficiency, but also to address longstanding inequalities in access to healthcare.

Keywords

Artificial intelligence, AI augmented radiology, diagnostic imaging, healthcare inequality, resource constrained settings, tele radiology, India

Publication Information

Publication Type Full Manuscript
Publication Date 24/09/2026
Volume 1

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