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Published on: September 28, 2022
AI solutions to the radiology workforce shortage
Andrew B Jing1, Naveen Garg1, Jiajie Zhang2
1Department of Abdominal Imaging, Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Npj Health Systems
|July 29, 2026
Summary
Artificial intelligence (AI) can help solve the radiology workforce shortage by improving efficiency and capacity. AI tools can manage demand, streamline workflows, and support radiologists, ensuring sustainable patient care.
Area of Science:
- Radiology
- Medical Imaging
- Artificial Intelligence
Background:
- Increasing demand for imaging services due to aging population and chronic diseases.
- Radiology workforce shortage exacerbated by limited residency positions and retirements.
- Imbalances lead to increased patient wait times, diagnostic delays, and radiologist burnout.
Purpose of the Study:
- To explore how artificial intelligence (AI) can address the radiology workforce shortage.
- To identify AI applications in demand management, workflow efficiency, and capacity building.
- To assess AI's potential for enhancing long-term workforce sustainability in radiology.
Main Methods:
- Review of AI applications in radiology.
- Analysis of AI's impact on demand, efficiency, and capacity.
- Evaluation of AI's role in education, collaboration, and patient communication.
Main Results:
- AI can reduce unnecessary imaging and prioritize high-value examinations through predictive analytics.
- AI tools can automate scheduling, assist in report generation, and perform image quality checks.
- AI enhances radiologist capabilities, improves retention, and supports workforce sustainability.
Conclusions:
- AI offers a multi-faceted solution to the radiology workforce shortage.
- Integrating AI can optimize demand, boost efficiency, and build capacity in radiology.
- AI implementation is crucial for maintaining high standards of patient care amidst workforce challenges.
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