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The role of radiologists is evolving with artificial intelligence (AI) and big data, shifting towards extracting comprehensive information from imaging, even without specific clinical questions. This necessitates new workflows and guidelines for AI-assisted prognostication and high-value care.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • The traditional role of radiologists involves answering specific clinical questions to aid treatment decisions.
  • Forces such as artificial intelligence (AI), big data analytics, and advanced imaging technologies are rapidly transforming radiology.
  • A new paradigm is emerging where radiologists, alongside AI, will extract maximum information from imaging data.

Purpose of the Study:

  • To review the evolving role of radiologists in the era of AI and big data.
  • To discuss the challenges and opportunities presented by AI-assisted prognostication and information extraction.
  • To emphasize the importance of ensuring high-value care in modern radiology practice.

Main Methods:

  • Review of current trends and advancements in radiology.
  • Analysis of the impact of artificial intelligence and big data on radiological workflows.
  • Discussion of emerging AI applications, including prognostication from imaging data.

Main Results:

  • AI and big data enable radiologists to extract more information from imaging, predict long-term outcomes (AI-assisted prognostication), and operate beyond specific clinical questions.
  • The integration of AI necessitates streamlined workflows, improved communication, and robust data management.
  • Emerging issues include reimbursement, liability, and equitable patient access to new technologies.

Conclusions:

  • Radiologists' roles are expanding beyond traditional diagnostic interpretations to encompass comprehensive data extraction and AI-assisted prognostication.
  • Addressing challenges related to data management, reimbursement, liability, and access is crucial for integrating AI effectively.
  • Ensuring high-value care requires adapting practices and developing guidelines for the responsible use of AI in radiology.