A study evaluates generative AI's performance in interpreting chest X-rays for tuberculosis screening in low-resource settings.
Key Details
- 1Researchers trained a generative AI model using two public TB chest radiograph datasets.
- 2The AI generated free-text reports and labeled images as showing presence/absence and laterality of TB-related abnormalities.
- 3Radiologists compared the model's reports to their own interpretations and judged report acceptability.
- 4Two additional radiologists established the reference standard for evaluation.
- 5Generative AI shows promise but still needs significant oversight before clinical deployment.
Why It Matters
Automating TB screening with generative AI could address radiologist shortages, especially in high-prevalence, low-resource settings. However, the need for oversight highlights ongoing challenges around accuracy, reliability, and safe adoption in clinical workflows.
Source
Health Imaging
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