A Nature Communications paper reports an automated MRI system that reliably detects clinically significant prostate cancer, reducing dependence on specialist radiologists. The model integrates MRI sequences and an automated workflow to segment lesions and assign risk, showing performance consistent with expert reads in multicenter validation. The system could streamline diagnostics in community settings and standardize selection for biopsy and active surveillance.