Enhancing Radiologist Productivity with Artificial Intelligence in Magnetic Resonance Imaging (MRI): A Narrative Review
importance 5/10
ai assisted
Artificial Intelligence in Healthcare and Education radiology stage: research
Problem
Radiologists face heavy MRI workloads with long scanning and reading times; the review asks whether AI can improve productivity.
Why it matters
Radiologist workload and diagnostic delays affect patient care quality and cost.
What the AI did
A narrative review synthesized 67 studies on AI shortening scan/reading times, optimizing worklist triage, and automating segmentation.
Results
not stated in source
Impact
Evidence synthesis suggests AI can streamline MRI workflows, per reviewed studies.
Record
| Venue | Diagnostics |
|---|---|
| Published | 2025 |
| Work type | review |
| Authors | Arun Nair, Wilson Ong, Aric Lee, Naomi Wenxin Leow, Andrew Makmur, Yong Han Ting, You Jun Lee, Shao Jin Ong et al. |
| Citations | 30 (OpenAlex, at import time) |
| References | 174 |
| Model or method | not stated in source |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/diagnostics15091146 |
| Open access | gold |
| Keywords | AI, MRI, radiologist productivity, worklist triage, segmentation, review |
Importance rating
5
real but narrower advance
Abstract notes MRI's extensive clinical use and that AI may reduce radiologist workload and improve diagnostic accuracy; synthesis of 67 studies, but no quantified scale.