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. 2026 May 22;17:1832572. doi: 10.3389/fpsyg.2026.1832572

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Copyright © 2026 Xu and Xia.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Diagram illustrating a Generative Adversarial Network workflow where random noise and latent space images enter a generator, producing images evaluated by a discriminator, which compares them to real samples and outputs true or false. — Adversarial network model for healing content generation.