09-05-2024 | Artificial Intelligence | Opinion
Managing expectations and challenges of AI in radiology
Author:
Frederick J. A. Meijer
Published in:
European Radiology
|
Issue 11/2024
Login to get access
Excerpt
The artificial intelligence (AI) revolution is both impressive and exhilarating, as AI is already making profound changes in healthcare and radiology. Its potential advantages are evident, enhancing radiological processes across the board, from image acquisition and reporting to Computer-Aided Diagnosis (CAD) and treatment decision-making [
1,
2]. However, it is essential to recognize that AI solutions are tools, not magic. They come with limitations and pitfalls, including overfitting, model drift, and automation bias [
3,
4]. End-users must be well-acquainted with these aspects. An important point to stress is that AI is not a purpose in itself, but rather a means to enhance radiological workflows and to benefit end-users and patient outcomes. Ultimately, in clinical practice, it is the combination of domain expertise and compassionate human care that truly matters. …