ArticlemedRxiv : the preprint server for health sciences2025
The Effect of AI on the Radiologist Workforce: A Task-Based Analysis.
Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
Background: The effect of AI algorithms on the radiology workforce has been a subject of commentary and controversy. There is now sufficient published evidence to support a quantitative task-based analysis to predict these effects. Purpose: To construct a quantitative, task-based model to predict the effect of AI on the radiology workforce using the best available evidence. Materials and Methods: We reviewed the literature to establish the tasks on which radiologists spend their time. We then developed categories of AI applications that could affect these tasks. We used published evidence to estimate the effect of each AI application on each radiology task using a 5-year time horizon. When published evidence was unavailable, we used our own judgment. Results: The model projects a 33% reduction in hours worked by radiologists in 5 years, with a range of 14% to 49%. The main effects are due to radiology report drafting for all modalities and study delegation for radiography and mammography. Conclusion: AI applications likely will cause a significant decrease in radiologist hours worked.. Given the relatively static radiology workforce and the continued growth in imaging volumes, radiologist job loss is unlikely for the foreseeable future.
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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.