AIMC Topic: Confidentiality
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High-reward, high-risk technologies? An ethical and legal account of AI development in healthcare.
BMC medical ethics
Jan 15, 2025
BACKGROUND: Considering the disruptive potential of AI technology, its current and future impact in healthcare, as well as healthcare professionals' lack of training in how to use it, the paper summarizes how to approach the challenges of AI from an ...
Deep learning-based encryption scheme for medical images using DCGAN and virtual planet domain.
Scientific reports
Jan 7, 2025
The motivation for this article stems from the fact that medical image security is crucial for maintaining patient confidentiality and protecting against unauthorized access or manipulation. This paper presents a novel encryption technique that integ...
Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges.
International journal of medical informatics
Dec 30, 2024
INTRODUCTION: Artificial Intelligence is in the phase of health care, with transformative innovations in diagnostics, personalized treatment, and operational efficiency. While having potential, critical challenges are apparent in areas of safety, tru...
Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation.
Computer methods and programs in biomedicine
Dec 28, 2024
BACKGROUND: Data sharing in healthcare is vital for advancing research and personalized medicine. However, the process is hindered by privacy, ethical, and legal challenges associated with patient data. Synthetic data generation emerges as a promisin...
Healthcare ethics and artificial intelligence: a UK doctor survey.
BMJ open
Dec 20, 2024
OBJECTIVES: To survey UK doctors on their uses of artificial intelligence (AI) and of their views on the ethics and regulation of AI in healthcare.
The urgent need to accelerate synthetic data privacy frameworks for medical research.
The Lancet. Digital health
Nov 26, 2024
Synthetic data, generated through artificial intelligence technologies such as generative adversarial networks and latent diffusion models, maintain aggregate patterns and relationships present in the real data the technologies were trained on withou...
Towards regulatory generative AI in ophthalmology healthcare: a security and privacy perspective.
The British journal of ophthalmology
Sep 20, 2024
As the healthcare community increasingly harnesses the power of generative artificial intelligence (AI), critical issues of security, privacy and regulation take centre stage. In this paper, we explore the security and privacy risks of generative AI ...
Artificial intelligence and health-related data: The patient's best interest and data ownership dilemma.
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Sep 14, 2024
The rapid advancement of artificial intelligence (AI) in healthcare has the potential to revolutionize the global healthcare sector and medicine in general. However, integrating AI technologies in healthcare requires access to large amounts of person...
Data privacy-aware machine learning approach in pancreatic cancer diagnosis.
BMC medical informatics and decision making
Sep 5, 2024
PROBLEM: Pancreatic ductal adenocarcinoma (PDAC) is considered a highly lethal cancer due to its advanced stage diagnosis. The five-year survival rate after diagnosis is less than 10%. However, if diagnosed early, the five-year survival rate can reac...
Biomedical Data Science, Artificial Intelligence, and Ethics: Navigating Challenges in the Face of Explosive Growth.
Annual review of biomedical data science
Jul 24, 2024
Advances in biomedical data science and artificial intelligence (AI) are profoundly changing the landscape of healthcare. This article reviews the ethical issues that arise with the development of AI technologies, including threats to privacy, data s...
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