Clinical acceptance of software based on artificial intelligence technologies (radiology)
This addresses the need for standardized evaluation of AI tools in radiology to ensure clinical safety and regulatory compliance, but it is incremental as it builds on existing clinical testing processes.
The authors developed a methodological framework for clinical testing, acceptance, and assessment of AI-based software in radiology, focusing on evaluating accuracy and efficiency as part of preparation for medical product registration.
Aim: provide a methodological framework for the process of clinical tests, clinical acceptance, and scientific assessment of algorithms and software based on the artificial intelligence (AI) technologies. Clinical tests are considered as a preparation stage for the software registration as a medical product. The authors propose approaches to evaluate accuracy and efficiency of the AI algorithms for radiology.