Through interviews with four leading European radiologists, this series examines the current state and future of AI-assisted reading in radiology.
From debunking the replacement myth, to understanding adoption barriers, to clinical evidence in lung cancer screening — in three parts.
Contributing Experts
Prof. Martine Remy-Jardin | Thoracic Imaging Specialist, France
President-Elect, Fleischner Society (2027)
Prof. Dr. med. Jens Vogel-Claussen | Director, Department of Radiology
Charité – Universitätsmedizin Berlin
Prof. Marie-Pierre Revel | Professor of Radiology
Hôpital Cochin, Université de Paris
Dr. Luis Gorospe | Radiologist
Ramón y Cajal University Hospital, Madrid |
PART 1 Myths vs. Reality
AI in Radiology: Why Collaboration, Not Replacement, Is the Answer
As artificial intelligence has made its way into medical imaging, the prediction that “radiologists will be replaced by AI” has been repeated time and again. This narrative has influenced everything from medical students’ specialty choices to hospital technology investment decisions.
However, European radiologists who are actively using AI-assisted reading in clinical practice disagree with this prediction. This article examines three common misconceptions about AI in radiology and presents what the experts actually have to say.
Myth 1: “Choosing Radiology as a Specialty Is Risky”
The concern that advancing AI would render radiologists obsolete was once seriously debated even among medical students. Prof. Martine Remy-Jardin makes clear that this “risk narrative” has not held up against reality.
“There were people suggesting it would be better not to choose radiology as a specialization. But the direction we are seeing now is not replacement — it is collaboration and advancement.”
— Martine Remy-Jardin, Thoracic Imaging Specialist, France President-Elect, Fleischner Society (2027)
In the view of frontline experts, technological progress is driving innovation in how work is done, not the elimination of the profession itself.
Myth 2: “AI Already Outperforms Radiologists”
As expectations for AI’s image analysis capabilities have grown, so has the perception that AI has already surpassed human specialists. Prof. Marie-Pierre Revel draws a clear line, calling this a myth at the current stage.
“AI is a complementary tool. There are certain lesions it can detect better than the human eye, but there are also cancers it still misses. For now, AI does not outperform radiologists.”
— Marie-Pierre Revel, Professor of Radiology Hôpital Cochin, Université de Paris
AI demonstrates strengths in specific areas, but it has not yet reached the stage of perfectly detecting all types of lesions. The term “complementary tool” most accurately describes AI’s current role.
Myth 3: “As AI Advances, the Doctor’s Role Will Diminish”
Some predict that as AI technology matures, there will be less room for physician involvement. Prof. Jens Vogel-Claussen argues the opposite — that AI’s advancement is actually expanding the physician’s role.
“AI is often called a ‘black box.’ It’s up to the radiologist to validate the results and confirm the findings. The final responsibility remains ours. Our role will evolve toward broader responsibilities.”
— Jens Vogel-Claussen, Director, Department of Radiology Charité – Universitätsmedizin Berlin
[Watch the Full Interview] Click here to see the experts discuss the future of AI in radiology.
Even as AI automates analysis, the verification and final judgment of results remain firmly in the physician’s domain. AI’s advancement contributes to enhancing reading efficiency and accuracy, not to reducing the doctor’s role.
➤ In PART 2, we examine the real-world barriers to AI adoption — reimbursement, regulation, and trust — and how they are being addressed.
⚠ Disclaimer: Expert statements in this document represent each interviewee’s academic and clinical views and do not constitute endorsement or recommendation of any specific product. AI-based software does not replace diagnosis; final clinical judgment remains with the physician.
List