Opportunity and Opportunism in Artificial Intelligence-Powered Data Extraction: A Value-Centered Approach.

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.