From Accuracy to Vulnerability: Quantifying the Impact of Adversarial Perturbations on Healthcare AI Models

As AI becomes indispensable in healthcare, its vulnerability to adversarial attacks demands serious attention. Even minimal changes to the input data can mislead Deep Learning (DL) models, leading to critical errors in diagnosis and endangering patient safety. In this study, we developed an optimize...

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Bibliographic Details
Main Authors: Sarfraz Brohi, Qurat-ul-ain Mastoi
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Big Data and Cognitive Computing
Subjects:
Online Access:https://www.mdpi.com/2504-2289/9/5/114
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