[HTML][HTML] Ethical challenges and solutions of generative AI: An interdisciplinary perspective

M Al-kfairy, D Mustafa, N Kshetri, M Insiew, O Alfandi - Informatics, 2024 - mdpi.com
Background: Open Access Systematic Review Ethical Challenges and Solutions of
Generative AI: An Interdisciplinary Perspective by Mousa Al-kfairy 1,*, Dheya Mustafa 2, Nir …

Deepfakes: An integrative review of the literature and an agenda for future research

PN Vasist, S Krishnan - … of the Association for Information Systems, 2022 - aisel.aisnet.org
We are witnessing a growing concern around the impact of hyper-realistic synthetic media
and its dissemination in what is widely known as" deepfakes." However, the phenomenon's …

A novel deep learning approach for deepfake image detection

A Raza, K Munir, M Almutairi - Applied Sciences, 2022 - mdpi.com
Deepfake is utilized in synthetic media to generate fake visual and audio content based on a
person's existing media. The deepfake replaces a person's face and voice with fake media …

General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance

I Triguero, D Molina, J Poyatos, J Del Ser, F Herrera - Information Fusion, 2024 - Elsevier
Abstract Most applications of Artificial Intelligence (AI) are designed for a confined and
specific task. However, there are many scenarios that call for a more general AI, capable of …

Diffusion-based conditional ECG generation with structured state space models

JML Alcaraz, N Strodthoff - Computers in biology and medicine, 2023 - Elsevier
Generating synthetic data is a promising solution for addressing privacy concerns that arise
when distributing sensitive health data. In recent years, diffusion models have become the …

DeepFake knee osteoarthritis X-rays from generative adversarial neural networks deceive medical experts and offer augmentation potential to automatic classification

F Prezja, J Paloneva, I Pölönen, E Niinimäki… - Scientific Reports, 2022 - nature.com
Recent developments in deep learning have impacted medical science. However, new
privacy issues and regulatory frameworks have hindered medical data sharing and …

ME-GAN: Learning panoptic electrocardio representations for multi-view ECG synthesis conditioned on heart diseases

J Chen, K Liao, K Wei, H Ying… - … on Machine Learning, 2022 - proceedings.mlr.press
Electrocardiogram (ECG) is a widely used non-invasive diagnostic tool for heart diseases.
Many studies have devised ECG analysis models (eg, classifiers) to assist diagnosis. As an …

Synthetic data in healthcare

D McDuff, T Curran, A Kadambi - arxiv preprint arxiv:2304.03243, 2023 - arxiv.org
Synthetic data are becoming a critical tool for building artificially intelligent systems.
Simulators provide a way of generating data systematically and at scale. These data can …

Golden standard or obsolete method? Review of ECG applications in clinical and experimental context

T Stracina, M Ronzhina, R Redina… - Frontiers in …, 2022 - frontiersin.org
Cardiovascular system and its functions under both physiological and pathophysiological
conditions have been studied for centuries. One of the most important steps in the …

[HTML][HTML] Generative adversarial networks in electrocardiogram synthesis: Recent developments and challenges

L Berger, M Haberbusch, F Moscato - Artificial Intelligence in Medicine, 2023 - Elsevier
Training deep neural network classifiers for electrocardiograms (ECGs) requires sufficient
data. However, imbalanced datasets pose a major problem for the training process and …