Evidence record 12737 · automatically gathered

On the fragility of neural architecture search: the role of overfitting and task complexity in medical image analysis

IntroductionNeural Architecture Search (NAS) effectively automates Deep Learning pipeline design but is prone to validation overfitting when applied to complex tasks, such as medical image analysis. To mitigate this and enhance generalization, researchers frequently integrate Deep Ensemble Learning (DEL) and data augmentation into the NAS workflow. However, the assumption that these methodologies do not negatively interfere in high-overfitting scenarios remains unproven.MethodsWe evaluated NAS,

Record details

Published: 22 July 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Healthcare
Retrieved: 23 July 2026

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ethics.ai (22 July 2026), “On the fragility of neural architecture search: the role of overfitting and task complexity in medical image analysis,” evidence record 12737, https://ethics.ai/record/12737 (originally published by Frontiers in Artificial Intelligence).

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