The architectural gap in clinical artificial intelligence

This is the authors' abstract. We don't add key points for this paper.

In The Lancet Digital Health, a systematic review and meta-analysis by Alabed Samer and colleagues1 provides a clear picture about the current state of clinical artificial intelligence (AI) in radiology communication. Across patients, members of the public, and clinicians, large language model-generated simplifications of radiology reports were consistently rated as more understandable than original reports, while maintaining high clinician-rated accuracy and completeness. At the same time, the meta-analysis presents persistent concerns around releasability, safety, and the absence of real-world deployment data.