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Privacy

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Compressed gastric image generation based on soft-label dataset distillation for medical data sharing.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE:   Sharing of medical data is required to enable the cross-agency flow of healthcare information and construct high-accuracy computer-aided diagnosis systems. However, the large sizes of medical datasets, the massive amount o...

IIB-CPE: Inter and Intra Block Processing-Based Compressible Perceptual Encryption Method for Privacy-Preserving Deep Learning.

Sensors (Basel, Switzerland)
Perceptual encryption (PE) of images protects visual information while retaining the intrinsic properties necessary to enable computation in the encryption domain. Block-based PE produces JPEG-compliant images with almost the same compression savings...

Deep Learning for Encrypted Traffic Classification and Unknown Data Detection.

Sensors (Basel, Switzerland)
Despite the widespread use of encryption techniques to provide confidentiality over Internet communications, mobile device users are still susceptible to privacy and security risks. In this paper, a novel Deep Neural Network (DNN) based on a user act...

Recover User's Private Training Image Data by Gradient in Federated Learning.

Sensors (Basel, Switzerland)
Exchanging gradient is a widely used method in modern multinode machine learning system (e.g., distributed training, Federated Learning). Gradients and weights of model has been presumed to be safe to delivery. However, some studies have shown that g...

Next-Generation Capabilities in Trusted Research Environments: Interview Study.

Journal of medical Internet research
BACKGROUND: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (principles and standards), providing access to data for research while protecting patient confidentiality....

A digital mask to safeguard patient privacy.

Nature medicine
The storage of facial images in medical records poses privacy risks due to the sensitive nature of the personal biometric information that can be extracted from such images. To minimize these risks, we developed a new technology, called the digital m...

Multimodal biomedical AI.

Nature medicine
The increasing availability of biomedical data from large biobanks, electronic health records, medical imaging, wearable and ambient biosensors, and the lower cost of genome and microbiome sequencing have set the stage for the development of multimod...

Analysis of the Exploration of Security and Privacy for Healthcare Management Using Artificial Intelligence: Saudi Hospitals.

Computational intelligence and neuroscience
A large component of the Health Information Systems now comprises numerous independent apps created in the past that need to be merged to provide a more uniform service. In addition to affecting the Intelligent Health Board Functionality and dependab...

An investigation of privacy preservation in deep learning-based eye-tracking.

Biomedical engineering online
BACKGROUND: The expanding usage of complex machine learning methods such as deep learning has led to an explosion in human activity recognition, particularly applied to health. However, complex models which handle private and sometimes protected data...

Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects.

Computers in biology and medicine
Human Activity Recognition (HAR) plays a significant role in the everyday life of people because of its ability to learn extensive high-level information about human activity from wearable or stationary devices. A substantial amount of research has b...