VICCA: Visual interpretation and comprehension of chest X-ray anomalies in generated report without human feedback
As artificial intelligence (AI) becomes increasingly central to healthcare, the demand for explainable and trustworthy models is paramount. Current report generation systems for chest X-rays (CXR) often lack mechanisms for validating outputs without expert oversight, raising concerns about reliabili...
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| Main Authors: | Sayeh Gholipour Picha, Dawood Al Chanti, Alice Caplier |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827025000672 |
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