AIMC Topic: Privacy

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A federated learning-based privacy-preserving image processing framework for brain tumor detection from CT scans.

Scientific reports Jul 2, 2025
The detection of brain tumors is crucial in medical imaging, because accurate and early diagnosis can have a positive effect on patients. Because traditional deep learning models store all their data together, they raise questions about privacy, comp...
Algorithms Tomography, X-Ray Computed Humans Neural Networks, Computer Image Processing, Computer-Assisted Privacy Federated Learning Brain Neoplasms Deep Learning
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An explainable federated blockchain framework with privacy-preserving AI optimization for securing healthcare data.

Scientific reports Jul 1, 2025
With the rapid growth of healthcare data and the need for secure, interpretable, and decentralized machine learning systems, Federated Learning (FL) has emerged as a promising solution. However, FL models often face challenges regarding privacy prese...
Algorithms Delivery of Health Care Computer Security Blockchain Privacy Artificial Intelligence Humans Machine Learning
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Balancing privacy and health integrity: A novel framework for ECG signal analysis in immersive environments.

Computers in biology and medicine May 1, 2025
The widespread use of immersive technologies such as Virtual Reality, Mixed Reality, and Augmented Reality has led to the continuous collection and streaming of vast amounts of sensitive biometric data. Among the biometric signals collected, ECG (ele...
Privacy Humans Algorithms Signal Processing, Computer-Assisted Confidentiality Electrocardiography
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A combined approach of evolutionary game and system dynamics for user privacy protection in human intelligence interaction.

Scientific reports Apr 21, 2025
The rapid development of generative artificial intelligence (GenAI) has generated significant economic and social value, alongside risks to user privacy. For this purpose, this study investigates privacy protection in human-AI interaction by employin...
Privacy Game Theory Humans Artificial Intelligence
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Federated Learning in radiomics: A comprehensive meta-survey on medical image analysis.

Computer methods and programs in biomedicine Apr 19, 2025
Federated Learning (FL) has emerged as a promising approach for collaborative medical image analysis while preserving data privacy, making it particularly suitable for radiomics tasks. This paper presents a systematic meta-analysis of recent surveys ...
Machine Learning Algorithms Humans Image Processing, Computer-Assisted Diagnostic Imaging Privacy Radiomics Surveys and Questionnaires Federated Learning
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Federated learning with differential privacy for breast cancer diagnosis enabling secure data sharing and model integrity.

Scientific reports Apr 16, 2025
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...
Female Breast Neoplasms Privacy Computer Security Information Dissemination Confidentiality Humans Federated Learning Machine Learning
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Privacy-preserving federated learning for collaborative medical data mining in multi-institutional settings.

Scientific reports Apr 11, 2025
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...
Confidentiality Privacy Humans Federated Learning Magnetic Resonance Imaging Data Mining
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A study on innovation resistance of artificial intelligence voice assistants based on privacy infringement and risk perception.

PloS one Apr 8, 2025
As a vital tool for human-computer interaction, artificial intelligence (AI) voice assistants have become an integral part of individuals' everyday routines. However, there are still a series of problems caused by privacy violations in current use. T...
Voice Adult Female Privacy Young Adult Middle Aged Speech Recognition Software Male Humans Artificial Intelligence
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DEeR: Deviation Eliminating and Noise Regulating for Privacy-Preserving Federated Low-Rank Adaptation.

IEEE transactions on medical imaging Apr 3, 2025
Integrating low-rank adaptation (LoRA) with federated learning (FL) has received widespread attention recently, aiming to adapt pretrained foundation models (FMs) to downstream medical tasks via privacy-preserving decentralized training. However, owi...
Image Processing, Computer-Assisted Privacy Machine Learning Algorithms Humans
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Model interpretability on private-safe oriented student dropout prediction.

PloS one Mar 31, 2025
Student dropout is a significant social issue with extensive implications for individuals and society, including reduced employability and economic downturns, which, in turn, drastically influence social sustainable development. Identifying students ...
Machine Learning Student Dropouts Deep Learning Humans Students Privacy
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