Heterogeneity and predictors of the effects of AI assistance on radiologists
The integration of artificial intelligence (AI) in medical image interpretation requires effective collaboration between clinicians and AI algorithms. Although previous studies demonstrated the potential of AI assistance in improving overall clinician performance, the individual impact on clinicians remains unclear. This large-scale study examined the heterogeneous effects of AI assistance on 140 radiologists across 15 chest X-ray diagnostic tasks and identified predictors of these effects. Surp
Record details
Published: 1 March 2024
Source: OpenAlex
Category: Research
Topics: Healthcare
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (1 March 2024), “Heterogeneity and predictors of the effects of AI assistance on radiologists,” evidence record 9655, https://ethics.ai/record/9655 (originally published by OpenAlex).
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