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Synthetic data generation: State of the art in health care domain
Recent progress in artificial intelligence and machine learning has led to the growth of
research in every aspect of life including the health care domain. However, privacy risks and …
research in every aspect of life including the health care domain. However, privacy risks and …
Reforms: Consensus-based recommendations for machine-learning-based science
Machine learning (ML) methods are proliferating in scientific research. However, the
adoption of these methods has been accompanied by failures of validity, reproducibility, and …
adoption of these methods has been accompanied by failures of validity, reproducibility, and …
Brain imaging generation with latent diffusion models
Deep neural networks have brought remarkable breakthroughs in medical image analysis.
However, due to their data-hungry nature, the modest dataset sizes in medical imaging …
However, due to their data-hungry nature, the modest dataset sizes in medical imaging …
[HTML][HTML] Data-driven energy management of virtual power plants: A review
A virtual power plant (VPP) refers to an active aggregator of heterogeneous distributed
energy resources (DERs), which creates a promising pathway to expand renewable energy …
energy resources (DERs), which creates a promising pathway to expand renewable energy …
[HTML][HTML] What does DALL-E 2 know about radiology?
Generative models, such as DALL-E 2 (OpenAI), could represent promising future tools for
image generation, augmentation, and manipulation for artificial intelligence research in …
image generation, augmentation, and manipulation for artificial intelligence research in …
Learning from data with structured missingness
Missing data are an unavoidable complication in many machine learning tasks. When data
are 'missing at random'there exist a range of tools and techniques to deal with the issue …
are 'missing at random'there exist a range of tools and techniques to deal with the issue …
Realistic morphology-preserving generative modelling of the brain
Medical imaging research is often limited by data scarcity and availability. Governance,
privacy concerns and the cost of acquisition all restrict access to medical imaging data …
privacy concerns and the cost of acquisition all restrict access to medical imaging data …
Synthetic data as an enabler for machine learning applications in medicine
Synthetic data generation is the process of using machine learning methods to train a model
that captures the patterns in a real dataset. Then new or synthetic data can be generated …
that captures the patterns in a real dataset. Then new or synthetic data can be generated …
Real risks of fake data: Synthetic data, diversity-washing and consent circumvention
Machine learning systems require representations of the real world for training and testing-
they require data, and lots of it. Collecting data at scale has logistical and ethical challenges …
they require data, and lots of it. Collecting data at scale has logistical and ethical challenges …
Sok: Privacy-preserving data synthesis
As the prevalence of data analysis grows, safeguarding data privacy has become a
paramount concern. Consequently, there has been an upsurge in the development of …
paramount concern. Consequently, there has been an upsurge in the development of …