AIMC Topic: Privacy

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Privacy and artificial intelligence: challenges for protecting health information in a new era.

BMC medical ethics Sep 15, 2021
BACKGROUND: Advances in healthcare artificial intelligence (AI) are occurring rapidly and there is a growing discussion about managing its development. Many AI technologies end up owned and controlled by private entities. The nature of the implementa...
Humans Artificial Intelligence Privacy Computer Security Big Data Data Anonymization
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An Intelligent Control Model of Credit Line Computing in Intelligence Health-Care Systems.

Frontiers in public health Sep 10, 2021
Technologies such as machine learning and artificial intelligence have brought about a tremendous change to biomedical computing and intelligence health care. As a principal component of the intelligence healthcare system, the hospital information sy...
Artificial Intelligence Privacy Delivery of Health Care Intelligence Confidentiality Humans
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Ethical Considerations Associated with "Humanitarian Drones": A Scoping Literature Review.

Science and engineering ethics Aug 3, 2021
The use of drones (or unmanned aerial vehicles, UVAs) in humanitarian action has emerged rapidly in the last decade and continues to expand. These so-called 'humanitarian drones' represent the first wave of robotics applied in the humanitarian and de...
Privacy Humans Organizations Robotics
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Privacy preserving distributed learning classifiers - Sequential learning with small sets of data.

Computers in biology and medicine Jul 31, 2021
BACKGROUND: Artificial intelligence (AI) typically requires a significant amount of high-quality data to build reliable models, where gathering enough data within a single institution can be particularly challenging. In this study we investigated the...
Privacy Neural Networks, Computer Artificial Intelligence Machine Learning Algorithms Humans
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Rebirth of Distributed AI-A Review of eHealth Research.

Sensors (Basel, Switzerland) Jul 23, 2021
The envisioned smart city domains are expected to rely heavily on artificial intelligence and machine learning (ML) approaches for their operations, where the basic ingredient is data. Privacy of the data and training time have been major roadblocks ...
Telemedicine Privacy Humans Artificial Intelligence Machine Learning Forecasting
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F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes.

Sensors (Basel, Switzerland) Jul 20, 2021
With the advent of smart health, smart cities, and smart grids, the amount of data has grown swiftly. When the collected data is published for valuable information mining, privacy turns out to be a key matter due to the presence of sensitive informat...
Artificial Intelligence Algorithms Privacy Models, Theoretical Fuzzy Logic
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Gait-Based Implicit Authentication Using Edge Computing and Deep Learning for Mobile Devices.

Sensors (Basel, Switzerland) Jul 5, 2021
Implicit authentication mechanisms are expected to prevent security and privacy threats for mobile devices using behavior modeling. However, recently, researchers have demonstrated that the performance of behavioral biometrics is insufficiently accur...
Deep Learning Computers, Handheld Privacy Biometric Identification Gait
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Leveraging data and AI to deliver on the promise of digital health.

International journal of medical informatics Apr 10, 2021
Rising rates of NCDs threaten fragile healthcare systems in low- and middle-income countries. Fortunately, new digital technology provides tools to more effectively address the growing dual burden of disease. Two-thirds of the world's population subs...
Sustainable Development Artificial Intelligence Privacy Humans Private Sector Delivery of Health Care
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Voice-Controlled Intelligent Personal Assistants in Health Care: International Delphi Study.

Journal of medical Internet research Apr 9, 2021
BACKGROUND: Voice-controlled intelligent personal assistants (VIPAs), such as Amazon Echo and Google Home, involve artificial intelligence-powered algorithms designed to simulate humans. Their hands-free interface and growing capabilities have a wide...
Humans Artificial Intelligence Delivery of Health Care Aged Privacy Delphi Technique Voice
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FeARH: Federated machine learning with anonymous random hybridization on electronic medical records.

Journal of biomedical informatics Mar 9, 2021
Electrical medical records are restricted and difficult to centralize for machine learning model training due to privacy and regulatory issues. One solution is to train models in a distributed manner that involves many parties in the process. However...
Research Design Electronic Health Records Algorithms Machine Learning Privacy
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