AIMC Topic: Deception
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Hy-DeFake: Hypergraph neural networks for detecting fake news in online social networks.
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Nowadays social media is the primary platform for people to obtain news and share information. Combating online fake news has become an urgent task to reduce the damage it causes to society. Existing methods typically improve their fake news detectio...
AI-Assisted Deception and the Emerging Challenge of LLMs in Forensic Psychiatry.
The journal of the American Academy of Psychiatry and the Law
Jun 10, 2025
Generative artificial intelligence (AI), including the large language model ChatGPT, has introduced potential new opportunities and challenges to the practice of forensic psychiatry. These powerful AI-based tools may offer substantial benefits in adm...
Deep Learning-Based Synthetic Skin Lesion Image Classification.
Studies in health technology and informatics
Aug 22, 2024
Advances in general-purpose computers have enabled the generation of high-quality synthetic medical images that human eyes cannot differ between real and AI-generated images. To analyse the efficacy of the generated medical images, this study propose...
Addressing academic dishonesty caused by artificial intelligence tools.
Journal of public health (Oxford, England)
May 29, 2024
The rise of generative artificial intelligence and the threat of fake news and disinformation online: Perspectives from sexual medicine.
Investigative and clinical urology
May 1, 2024
ChatGPT and Forms of Deception.
Nursing science quarterly
Jul 1, 2023
The artificial intelligence (AI) chatbot ChatGPT movement has upset and permeated all aspects of the healthcare arena, including the discipline of nursing. The use of ChatGPT is ethically controversial. This article begins a discussion regarding the ...
Deception Mode: How Conversational AI Can Respect Patient Autonomy.
The American journal of bioethics : AJOB
May 1, 2023
Deepfake detection by human crowds, machines, and machine-informed crowds.
Proceedings of the National Academy of Sciences of the United States of America
Jan 4, 2022
The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask ...
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