AI Medical Compendium Topic

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Confidentiality

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HCAP: Hybrid cyber attack prediction model for securing healthcare applications.

PloS one
The rapid development and integration of interconnected healthcare devices and communication networks within the Internet of Medical Things (IoMT) have significantly enhanced healthcare services. However, this growth has also introduced new vulnerabi...

Attribute encryption access control method of high dimensional medical data based on fuzzy algorithm.

PloS one
The current approach to data access control predominantly utilizes blockchain technology. However, when dealing with high-dimensional medical data, the inherent transparency of blockchain conflicts with the necessity of protecting patient privacy. Co...

The potential of artificial intelligence to transform medicine.

Current opinion in pediatrics
PURPOSE OF REVIEW: Increased incorporation of artificial intelligence in medicine has raised questions regarding how it can enhance efficiency in concert with providing accurate medical information without violating patient privacy. Pediatricians sho...

Acceptance and Usage of AI Applications in Health-Focused NGOs.

Studies in health technology and informatics
BACKGROUND: AI applications promise to be a valuable tool for health-focused NGOs. While often operating with limited resources, these organizations recognize the potential of AI to streamline processes and support workflows through automation. Howev...

Federated learning with differential privacy for breast cancer diagnosis enabling secure data sharing and model integrity.

Scientific reports
In the digital age, privacy preservation is of paramount importance while processing health-related sensitive information. This paper explores the integration of Federated Learning (FL) and Differential Privacy (DP) for breast cancer detection, lever...

Bridging the gaps: Overcoming challenges of implementing AI in healthcare.

Med (New York, N.Y.)
Artificial intelligence (AI) in healthcare promises transformative advancements, from enhancing diagnostics to optimizing personalized treatments. Realizing its full potential, however, requires addressing key challenges, including explainability, bi...

Privacy-preserving federated learning for collaborative medical data mining in multi-institutional settings.

Scientific reports
Ensuring data privacy in medical image classification is a critical challenge in healthcare, especially with the increasing reliance on AI-driven diagnostics. In fact, over 30% of healthcare organizations globally have experienced a data breach in th...

Data Governance in Healthcare AI: Navigating the EU AI Act's Requirements.

Studies in health technology and informatics
The integration of Artificial Intelligence (AI) into healthcare has the potential to revolutionize patient care, diagnostics, and treatment planning. However, this integration also introduces significant challenges related to data governance, privacy...

Secure healthcare data sharing and attack detection framework using radial basis neural network.

Scientific reports
Secure medical data sharing and access control play a prominent role. However, it is still unclear how to provide a security architecture that can guarantee the privacy and safety of sensitive medical data. Existing methods are application-specific a...

Ethics From the Outset: Incorporating Ethical Considerations into the Artificial Intelligence and Technology Collaboratories for Aging Research Pilot Projects.

The journals of gerontology. Series A, Biological sciences and medical sciences
There is an urgent need to develop tools to enable older adults to live healthy, independent lives for as long as possible. To address this need, the National Institute on Aging (NIA) Artificial Intelligence and Technology Collaboratories (AITCs) for...