Myths and facts about artificial intelligence: why machine- and deep-learning will not replace interventional...

Area of Science:

• Medical Imaging and Artificial Intelligence
• Radiology and Machine Learning

Background:

• Artificial intelligence (AI) is rapidly advancing, impacting various medical fields.
• Radiology is a key area where machine learning (ML) is being integrated, leading to significant practice changes.
• Concerns exist about AI potentially making radiologists obsolete.

Purpose of the Study:

• To examine the factual standing of AI in medicine and radiology.
• To address and debunk prevalent myths regarding the future role of radiologists in an AI-driven landscape.
• To provide a clear perspective on AI's actual capabilities and limitations in clinical practice.

Main Methods:

• Review and analysis of current AI applications in radiology.
• Critical evaluation of existing literature and expert opinions on AI's impact.
• Identification and refutation of common misconceptions surrounding AI and radiology.

Main Results:

• AI's current capabilities in radiology are significant but do not equate to full autonomy.
• Many fears of AI replacing radiologists are based on misunderstandings of the technology.
• AI serves as a tool to augment, not replace, the expertise of human radiologists.

Conclusions:

• AI is a powerful adjunct in radiology, enhancing diagnostic accuracy and efficiency.
• The future of radiology involves collaboration between human expertise and AI tools.
• AI will likely evolve the role of radiologists, rather than eliminate it.