Synthetic data generation: State of the art in health care domain

H Murtaza, M Ahmed, NF Khan, G Murtaza… - Computer Science …, 2023‏ - Elsevier
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 …

Reforms: Consensus-based recommendations for machine-learning-based science

S Kapoor, EM Cantrell, K Peng, TH Pham, CA Bail… - Science …, 2024‏ - science.org
Machine learning (ML) methods are proliferating in scientific research. However, the
adoption of these methods has been accompanied by failures of validity, reproducibility, and …

Brain imaging generation with latent diffusion models

WHL Pinaya, PD Tudosiu, J Dafflon… - MICCAI Workshop on …, 2022‏ - Springer
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 …

[HTML][HTML] Data-driven energy management of virtual power plants: A review

G Ruan, D Qiu, S Sivaranjani, ASA Awad… - Advances in Applied …, 2024‏ - Elsevier
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 …

[HTML][HTML] What does DALL-E 2 know about radiology?

LC Adams, F Busch, D Truhn, MR Makowski… - Journal of Medical …, 2023‏ - jmir.org
Generative models, such as DALL-E 2 (OpenAI), could represent promising future tools for
image generation, augmentation, and manipulation for artificial intelligence research in …

Learning from data with structured missingness

R Mitra, SF McGough, T Chakraborti… - Nature Machine …, 2023‏ - nature.com
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 …

Realistic morphology-preserving generative modelling of the brain

PD Tudosiu, WHL Pinaya… - Nature Machine …, 2024‏ - nature.com
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 …

Synthetic data as an enabler for machine learning applications in medicine

JF Rajotte, R Bergen, DL Buckeridge, K El Emam, R Ng… - Iscience, 2022‏ - cell.com
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 …

Real risks of fake data: Synthetic data, diversity-washing and consent circumvention

CD Whitney, J Norman - Proceedings of the 2024 ACM Conference on …, 2024‏ - dl.acm.org
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 …

Sok: Privacy-preserving data synthesis

Y Hu, F Wu, Q Li, Y Long, GM Garrido… - … IEEE Symposium on …, 2024‏ - ieeexplore.ieee.org
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 …