Generative adversarial networks in time series: A systematic literature review

E Brophy, Z Wang, Q She, T Ward - ACM Computing Surveys, 2023 - dl.acm.org
Generative adversarial network (GAN) studies have grown exponentially in the past few
years. Their impact has been seen mainly in the computer vision field with realistic image …

A survey of text representation and embedding techniques in nlp

R Patil, S Boit, V Gudivada, J Nandigam - IEEE Access, 2023 - ieeexplore.ieee.org
Natural Language Processing (NLP) is a research field where a language in consideration
is processed to understand its syntactic, semantic, and sentimental aspects. The …

[HTML][HTML] Estimating the success of re-identifications in incomplete datasets using generative models

L Rocher, JM Hendrickx, YA De Montjoye - Nature communications, 2019 - nature.com
While rich medical, behavioral, and socio-demographic data are key to modern data-driven
research, their collection and use raise legitimate privacy concerns. Anonymizing datasets …

Good proctor or “big brother”? Ethics of online exam supervision technologies

S Coghlan, T Miller, J Paterson - Philosophy & Technology, 2021 - Springer
Online exam supervision technologies have recently generated significant controversy and
concern. Their use is now booming due to growing demand for online courses and for off …

Synthetic data–anonymisation groundhog day

T Stadler, B Oprisanu, C Troncoso - 31st USENIX Security Symposium …, 2022 - usenix.org
Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data
publishing that addresses the shortcomings of traditional anonymisation techniques. The …

[HTML][HTML] The ethical, legal and social implications of using artificial intelligence systems in breast cancer care

SM Carter, W Rogers, KT Win, H Frazer, B Richards… - The Breast, 2020 - Elsevier
Breast cancer care is a leading area for development of artificial intelligence (AI), with
applications including screening and diagnosis, risk calculation, prognostication and clinical …

Anonymization: The imperfect science of using data while preserving privacy

A Gadotti, L Rocher, F Houssiau, AM Creţu… - Science …, 2024 - science.org
Information about us, our actions, and our preferences is created at scale through surveys or
scientific studies or as a result of our interaction with digital devices such as smartphones …

Ethical issues in using ambient intelligence in health-care settings

N Martinez-Martin, Z Luo, A Kaushal, E Adeli… - The lancet digital …, 2021 - thelancet.com
Ambient intelligence is increasingly finding applications in health-care settings, such as
hel** to ensure clinician and patient safety by monitoring staff compliance with clinical …

[HTML][HTML] Informed consent in biomedical research

FK Dankar, M Gergely, SK Dankar - Computational and structural …, 2019 - Elsevier
Informed consent is the result of tumultuous events in both the clinical and research arenas
over the last 100 years. Throughout this time, the notion of informed consent has shifted …

Ethical and regulatory challenges of AI technologies in healthcare: A narrative review

C Mennella, U Maniscalco, G De Pietro, M Esposito - Heliyon, 2024 - cell.com
Over the past decade, there has been a notable surge in AI-driven research, specifically
geared toward enhancing crucial clinical processes and outcomes. The potential of AI …