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Artificial intelligence in radiology: A comprehensive review study

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  • Hanady Elyas Osman

  • Rahaf Ahmed Alsahabi

  • Mejally Mohammed Kriri

  • Saddig Jastaniah

  • Mohamed Yousef

Abstract

Radiology has experienced a growing trend of interest and exploration in artificial intelligence (AI) research. It is seen as a promising tool for diagnosis and triage, but there are concerns about its implementation. Our main goal was to understand the true impact of AI in radiology and how it can be used to enhance the radiology workflow. This comprehensive review aimed to provide an overview of AI in radiology, explore AI ethics, and examine AI clinical applications. A total of 22 relevant articles from 2018 to 2024 were selected from the Internet based on specific search criteria, including keywords such as artificial intelligence, radiology, machine learning, and deep learning. This study focused on gathering information on the benefits and role of AI in facilitating workflow in a highly efficient and effective manner in various radiological modalities and their applications in medical areas. AI may progressively alter clinical practice by assisting radiologists in achieving better performance, interpreter dependability, and patient outcomes. Additionally, AI can help modify workflows to provide more timely recommendations. This review confirms that AI still faces some obstacles in radiology. However, we firmly believe that AI can have a positive influence on radiology if used as a supporting tool rather than a substitute for human expertise. It is important to recognize the value of AI as a tool for healthcare professionals that enhances their abilities and ultimately improves patient care and patient outcomes.

Suggested Citation

  • Hanady Elyas Osman & Rahaf Ahmed Alsahabi & Mejally Mohammed Kriri & Saddig Jastaniah & Mohamed Yousef, 2025. "Artificial intelligence in radiology: A comprehensive review study," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 8(7), pages 645-655.
  • Handle: RePEc:aac:ijirss:v:8:y:2025:i:7:p:645-655:id:10514
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