ReviewHealth and technology2025
The role of AI in mitigating the impact of radiologist shortages: a systematised review.
Review in Health and technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Artificial intelligence in health systems of the WHO European region: implementation, applications, opportunities, and barriers.International journal of medical informatics · 2026Article
- Artificial Intelligence for Detection and Characterisation of Bone Metastases on MRI: A Scoping Review.Cancers · 2026Review
- PancDS in Real-World Practice: A Prospective Multicenter Validation of a Clinical Decision-Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- How much radiologist time can be saved by implementing AI in screen-reading mammograms?European radiology · 2026Article
- Radiologist burnout: AI's true black box.European radiology · 2026Review
- Patient and Public Perceptions of Artificial Intelligence in Breast Imaging and Clinical Decision-Making: An Exploratory Cross-Sectional Survey Study.Diagnostics (Basel, Switzerland) · 2026Article
- Diagnostic accuracy of AI-assisted chest radiographs in tuberculosis screening: A Ghanaian clinical study.PloS one · 2026Article
- An Empirical Evaluation of Low-Rank Adapted Vision-Language Models for Radiology Image Captioning.Bioengineering (Basel, Switzerland) · 2025Article
- Review
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Purpose: This study aims to explore the application of Artificial intelligence (AI) systems in radiology departments and the role they play in the shortage of radiologists. It examines the ethical and legal considerations for uptake of AI both in relation to patient safety and for the profession of radiology. Methods: A systematised review was selected for this research study to collect maximum relevant evidence that provides a comprehensive overview of AI application in radiology specifically in terms of addressing radiologist shortages in hospitals. The search was complemented by grey literature to fill potential gaps. Results: Findings suggest that AI can read and interpret images more effectively and faster than radiologists and that it could be more widely used to reduce the impact of the global radiologist shortage, leading to better patient outcomes and safety. However, there are potential challenges predominantly ethical and legal. Concerns over complete radiologist replacement by AI do not currently seem likely, but rather the use of AI to complement radiologists in their work. Conclusions: AI cannot replace radiologists, instead radiology services will need the input of radiologists, AI systems and radiographers to provide a safe healthcare for all patients, therefore they are complementary. Radiologist jobs will most probably change to reduce repetitive tasks that can be conducted by AI. Radiologists and radiographers play a role in the provision of quality care in both normal day-to-day events and during times of disaster. Their role in diagnosing and prognosing diseases provides guidance during preparedness, response and recovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.