[HTML][HTML] Synthetic data generation methods in healthcare: A review on open-source tools and methods
Synthetic data generation has emerged as a promising solution to overcome the challenges
which are posed by data scarcity and privacy concerns, as well as, to address the need for …
which are posed by data scarcity and privacy concerns, as well as, to address the need for …
Empowerment of AI algorithms in biochemical sensors
Biochemical sensors have become indispensable tools for real-time, on-site monitoring and
analysis in diverse domains such as healthcare, environmental protection, and food safety …
analysis in diverse domains such as healthcare, environmental protection, and food safety …
Improving mixed-integer temporal modeling by generating synthetic data using conditional generative adversarial networks: A case study of fluid overload prediction …
Objective The challenge of mixed-integer temporal data, which is particularly prominent for
medication use in the critically ill, limits the performance of predictive models. The purpose …
medication use in the critically ill, limits the performance of predictive models. The purpose …
[HTML][HTML] Enhancing public research on citizen data: An empirical investigation of data synthesis using Statistics New Zealand's Integrated Data Infrastructure
Abstract The Integrated Data Infrastructure (IDI) in New Zealand is a critical asset that
integrates citizen data from various public and private organizations for population-level …
integrates citizen data from various public and private organizations for population-level …
Trustworthy AI for human-centric smart manufacturing: A survey
Human-centric smart manufacturing (HCSM) envisions a symbiotic relationship between
humans and machines, leveraging human capability and Artificial Intelligence (AI)'s …
humans and machines, leveraging human capability and Artificial Intelligence (AI)'s …
Systematic review of generative modelling tools and utility metrics for fully synthetic tabular data
Sharing data with third parties is essential for advancing science, but it is becoming more
and more difficult with the rise of data protection regulations, ethical restrictions, and growing …
and more difficult with the rise of data protection regulations, ethical restrictions, and growing …
Development of a synthetic dataset generation method for deep learning of real urban landscapes using a 3D model of a non-existing realistic city
In the urban landsca** field, training datasets for instance segmentation in the detection of
building facades are needed for complex analysis and simulation based on data. Manual …
building facades are needed for complex analysis and simulation based on data. Manual …
Prior-guided generative adversarial network for mammogram synthesis
Deep Learning is vital in medical imaging solutions and clinical applications. However,
multiple reasons, such as data scarcity and imbalance in the medical image dataset, cause …
multiple reasons, such as data scarcity and imbalance in the medical image dataset, cause …
Syntheval: a framework for detailed utility and privacy evaluation of tabular synthetic data
With the growing demand for synthetic data to address contemporary issues in machine
learning, such as data scarcity, data fairness, and data privacy, having robust tools for …
learning, such as data scarcity, data fairness, and data privacy, having robust tools for …
Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence
Clinical research relies on high-quality patient data, however, obtaining big data sets is
costly and access to existing data is often hindered by privacy and regulatory concerns …
costly and access to existing data is often hindered by privacy and regulatory concerns …