Enhancement attacks in biomedical machine learning. (arXiv:2301.01885v1 [stat.ML])

The prevalence of machine learning in biomedical research is rapidly growing,
yet the trustworthiness of such research is often overlooked. While some
previous works have investigated the ability of adversarial attacks to degrade
model performance in medical imaging, the ability to falsely improve
performance via recently-developed "enhancement attacks" may be a greater
threat to biomedical machine learning. In the spirit of developing attacks to
better understand trustworthiness, we developed three techniques to drastically
enhance prediction performance of classifiers with minimal …

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