ArticleNPJ digital medicine2026
Comparison of AI-generated radiology impressions: a multi-stakeholder evaluation.
Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
14 authors.
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Abstract
A retrospective, blinded evaluation of 200 oncologic computed tomography reports compared original radiologist-authored impressions, impressions generated by a custom domain-specific AI model fine-tuned on institutional data, and impressions generated by a general-purpose large language model. Ten clinicians, including original radiologists (n = 4), independent radiologists (n = 3), and oncologists (n = 3), rated impressions for completeness, correctness, conciseness, clarity, clinical utility, and patient harm. Original and independent radiologists assigned lower preference to generic model impressions (Cohen's h 1.04-1.22 and 0.66-0.69, p < 0.001). Original radiologists slightly preferred their own impressions to the custom model (h = 0.18, p = 0.0716), while independent radiologists showed no preference (h = -0.03, p = 0.78). Oncologists demonstrated no significant preference among impression types (h = 0.04-0.12, all p > 0.20). Custom model impressions achieved near parity with human impressions; original radiologists rated their own impressions slightly more complete (r = 0.22, p = 0.0016). Generic model impressions were longer (75.1 ± 20.4 words), slightly more complete (r = 0.18-0.39, p < 0.001-0.01), but significantly less concise (r = 0.85-0.87, p < 0.001). Patient harm ratings were uniformly low (likelihood 1.01-1.14; extent 1.05-1.21). Inter-rater reliability ranged from -0.09 to 0.67 (α = 0.67 conciseness; α = -0.09-0.03 clinical utility/correctness).
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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.