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The Role of Artificial Intelligence in Radiodiagnosis
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Author(s): Dipan Kumar Das (Centurion University of Technology and Management, India), Padmaja Patnaik (Centurion University of Technology and Management, India), Nibedita Nayak (Centurion University of Technology and Management, India)and Sudip Kumar Das (Dr. C.V. Raman University, India)
Copyright: 2026
Pages: 32
Source title:
Radiodiagnosis in the Era of AI
Source Author(s)/Editor(s): Praveen Kumar (Datta Meghe Institute of Higher Education and Research, Wardha, India), Prateek Verma (Dayananda Sagar University, Bangalore, India), Gaurav Vedprakash Mishra (Datta Meghe Institute of Higher Education and Research, Wardha, India), Gopal Singh Phartiyal (University of Leeds, UK)and Anurag Ashok Luharia (Datta Meghe Institute of Higher Education and Research, Wardha, India)
DOI: 10.4018/979-8-3373-0903-3.ch002
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Abstract
The integration of artificial intelligence (AI) into radio diagnosis is transforming the field by enhancing diagnostic accuracy, efficiency, and clinician workflow. AI-powered tools have demonstrated their potential to augment reader performance in interpreting chest radiographs, as evidenced by significant improvements in accuracy and time efficiency. Furthermore, AI-driven methodologies, such as deep learning algorithms, are being applied to detect complex pathologies, including COVID-19, fractures, and malignancies, with diagnostic accuracies rivalling or surpassing human radiologists. The implementation of AI in interventional radiology and radiotherapy planning has also introduced new opportunities for precision medicine, such as automated scoring and enhanced image quality for clinical decision-making. This chapter explores AI's role in radio diagnosis, highlighting its applications, benefits, and limitations. It addresses challenges like model generalizability, data bias. It also highlights the need for education and collaboration between radiologists and developers.
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