The architectural gap in clinical artificial intelligence
Abstract
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.
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Machine Learning in Healthcare
Genomics and Rare Diseases
Publication details
- Journal / source
- The Lancet Digital Health
- Publisher
- Elsevier BV
- Volume
- 8
- Issue
- 2
- Pages
- 100979–100979
- Publication date
- 1 February 2026
- Language
- EN