A Nature Communications paper described an automated MRI system that reliably identifies clinically significant prostate cancer, integrating image processing and machine learning to standardize detection. Authors Wu, Liu, and Yang validated the system against expert reads and multi‑center datasets and reported improvements in sensitivity and workflow efficiency. The technology targets reduction of inter‑reader variability and faster triage for biopsy decisions. Automated MRI refers to AI‑driven algorithms that pre‑process and score images to highlight suspicious lesions for radiologists.