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Foundation models struggle to generalize from adult to pediatric chest X-rays

By PulseAugur Editorial · [1 sources] ·

A new benchmark study published on arXiv evaluates the performance of six foundation models and two CNN baselines on chest X-ray classification tasks, specifically focusing on their ability to generalize from adult to pediatric data. The research found a significant performance drop, with Macro-AUROC scores decreasing from approximately 92% on adult data to around 78% on pediatric data. The study also indicated that increasing the depth of model adaptation did not substantially improve cross-population generalization, and strong performance on adult data did not predict better performance on pediatric data. AI

IMPACT Highlights the need for more robust foundation models in medical imaging, particularly for pediatric applications.

RANK_REASON Academic paper published on arXiv detailing a benchmark study of foundation models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Foundation models struggle to generalize from adult to pediatric chest X-rays

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Academic paper published on arXiv detailing a benchmark study of foundation models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Sara In\'acio, Hugo Proen\c{c}a, Jo\~ao C. Neves ·

    From Adults to Children: Benchmarking Foundation Models for Chest X-Ray Classification under Domain Shift

    arXiv:2610.21809v1 Announce Type: new Abstract: Foundation models have shown significant potential across diverse fields and have been applied to medical imaging, but their robustness across patient populations remains unclear. In this work, we investigate foundation models' abil…

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