AIMC Topic: Privacy

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A Federated Mining Approach on Predicting Diabetes-Related Complications: Demonstration Using Real-World Clinical Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
Chronic diabetes can lead to microvascular complications, including diabetic eye disease, diabetic kidney disease, and diabetic neuropathy. However, the long-term complications often remain undetected at the early stages of diagnosis. Developing a ma...
Machine Learning Humans Delivery of Health Care Diabetes Mellitus Confidentiality Privacy
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The spectrum of data sharing policies in neuroimaging data repositories.

Human brain mapping Feb 10, 2022
Sharing data is a scientific imperative that accelerates scientific discoveries, reinforces open science inquiry, and allows for efficient use of public investment and research resources. Considering these benefits, data sharing has been widely promo...
Artificial Intelligence Information Dissemination Policy Privacy Neuroimaging United States Humans
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A Graph Neural Network Based Decentralized Learning Scheme.

Sensors (Basel, Switzerland) Jan 28, 2022
As an emerging paradigm considering data privacy and transmission efficiency, decentralized learning aims to acquire a global model using the training data distributed over many user devices. It is a challenging problem since link loss, partial devic...
Linear Models Algorithms Privacy Computer Simulation Neural Networks, Computer
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Dynamic Asynchronous Anti Poisoning Federated Deep Learning with Blockchain-Based Reputation-Aware Solutions.

Sensors (Basel, Switzerland) Jan 17, 2022
As promising privacy-preserving machine learning technology, federated learning enables multiple clients to train the joint global model via sharing model parameters. However, inefficiency and vulnerability to poisoning attacks significantly reduce f...
Humans Machine Learning Privacy Blockchain Deep Learning Reproducibility of Results
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Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model.

Sensors (Basel, Switzerland) Jan 8, 2022
This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep learning model to make the technique non-invasive coupled with security preservation. Sensing and securing healthcare and medical images such as X-rays...
Pneumonia Deep Learning Privacy Bayes Theorem Neural Networks, Computer Algorithms Humans
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Ethical issues of smart home-based elderly care: A scoping review.

Journal of nursing management Dec 19, 2021
AIM: To explore current research on the ethics of smart home technologies including artificial intelligence and information technologies for elderly care by conducting a scoping review.
Privacy Aged Artificial Intelligence Humans
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Artificial Intelligence Is Safer for My Privacy: Interplay Between Types of Personal Information and Agents on Perceived Privacy Risk and Concerns.

Cyberpsychology, behavior and social networking Dec 9, 2021
The development of novel technologies has increasingly complicated the issue of users' privacy. This study aimed to investigate the impact that the types of information as well as agents have on perceptions of privacy risks and concerns. The results ...
Privacy Humans Artificial Intelligence Technology
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Is Homomorphic Encryption-Based Deep Learning Secure Enough?

Sensors (Basel, Switzerland) Nov 24, 2021
As the amount of data collected and analyzed by machine learning technology increases, data that can identify individuals is also being collected in large quantities. In particular, as deep learning technology-which requires a large amount of analysi...
Technology Humans Privacy Deep Learning Computer Security
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Federated personalized random forest for human activity recognition.

Mathematical biosciences and engineering : MBE Nov 22, 2021
User data usually exists in the organization or own local equipment in the form of data island. It is difficult to collect these data to train better machine learning models because of the General Data Protection Regulation (GDPR) and other laws. The...
Privacy Human Activities Machine Learning Humans
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Genetic CFL: Hyperparameter Optimization in Clustered Federated Learning.

Computational intelligence and neuroscience Nov 18, 2021
Federated learning (FL) is a distributed model for deep learning that integrates client-server architecture, edge computing, and real-time intelligence. FL has the capability of revolutionizing machine learning (ML) but lacks in the practicality of i...
Machine Learning Privacy Cluster Analysis Humans Algorithms Communication
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