Empowerment of AI algorithms in biochemical sensors
Z Zhou, T Xu, X Zhang - TrAC Trends in Analytical Chemistry, 2024 - Elsevier
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 …
[HTML][HTML] Can I trust my fake data–A comprehensive quality assessment framework for synthetic tabular data in healthcare
VB Vallevik, A Babic, SE Marshall, E Severin… - International Journal of …, 2024 - Elsevier
Background Ensuring safe adoption of AI tools in healthcare hinges on access to sufficient
data for training, testing and validation. Synthetic data has been suggested in response to …
data for training, testing and validation. Synthetic data has been suggested in response to …
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 …
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 landscaping 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 …
[HTML][HTML] 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 …
Privacy distillation: reducing re-identification risk of multimodal diffusion models
Knowledge distillation in neural networks refers to compressing a large model or dataset
into a smaller version of itself. We introduce Privacy Distillation, a framework that allows a …
into a smaller version of itself. We introduce Privacy Distillation, a framework that allows a …
[HTML][HTML] Deep learning-based approach in surface thermography for inverse estimation of breast tumor size
Z Khomsi, M Elfezazi, L Bellarbi - Scientific African, 2024 - Elsevier
Background and objective In early breast cancer diagnosis, tumor size is key to improving
the patient's survival chances. It helps doctors to determine the adequate treatment for each …
the patient's survival chances. It helps doctors to determine the adequate treatment for each …
Non-imaging medical data synthesis for trustworthy AI: A comprehensive survey
X Xing, H Wu, L Wang, I Stenson, M Yong… - ACM Computing …, 2024 - dl.acm.org
Data quality is a key factor in the development of trustworthy AI in healthcare. A large volume
of curated datasets with controlled confounding factors can improve the accuracy …
of curated datasets with controlled confounding factors can improve the accuracy …