讨论文件:医疗人工智能的完整性

Yisroel Mirsky
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引用次数: 1

摘要

深度学习已经被证明是医学界不可思议的财富。然而,有了攻击性的人工智能,这项技术可以用来对付医学界;对抗性样本可以被用来造成误诊,医学深度造假可以被用来欺骗放射科医生和机器。在这篇简短的讨论文章中,我们从医疗保健的角度来讨论攻击性人工智能的问题。我们讨论了该领域的国防研究人员如何应对威胁及其当前的挑战。最后,我们认为传统的安全机制比基于算法的解决方案更能缓解这些威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discussion Paper: The Integrity of Medical AI
Deep learning has proven itself to be an incredible asset to the medical community. However, with offensive AI, the technology can be turned against medical community; adversarial samples can be used to cause misdiagnosis and medical deepfakes can be used fool both radiologists and machines alike. In this short discussion paper, we talk about the issue of offensive AI and from the perspective of healthcare. We discuss how defense researchers in this domain have responded to the threat and their the current challenges. We conclude by arguing that conventional security mechanisms are a better approach towards mitigating these threats over algorithm based solutions.
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