[HTML][HTML] Challenges and opportunities of generative models on tabular data
Tabular data, organized like tables with rows and columns, is widely used. Existing models
for tabular data synthesis often face limitations related to data size or complexity. In contrast …
for tabular data synthesis often face limitations related to data size or complexity. In contrast …
GAN-Based Tabular Data Generator for Constructing Synopsis in Approximate Query Processing: Challenges and Solutions
In data-driven systems, data exploration is imperative for making real-time decisions.
However, big data are stored in massive databases that are difficult to retrieve. Approximate …
However, big data are stored in massive databases that are difficult to retrieve. Approximate …
Evaluating the performance of automated machine learning (AutoML) tools for heart disease diagnosis and prediction
LM Paladino, A Hughes, A Perera, O Topsakal… - AI, 2023 - mdpi.com
Globally, over 17 million people annually die from cardiovascular diseases, with heart
disease being the leading cause of mortality in the United States. The ever-increasing …
disease being the leading cause of mortality in the United States. The ever-increasing …
Evaluating the Utility and Privacy of Synthetic Breast Cancer Clinical Trial Data Sets
PURPOSE There is strong interest from patients, researchers, the pharmaceutical industry,
medical journal editors, funders of research, and regulators in sharing clinical trial data for …
medical journal editors, funders of research, and regulators in sharing clinical trial data for …
[HTML][HTML] Automating attendance management in human resources: A design science approach using computer vision and facial recognition
Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for
detecting objects in images and videos. Unlike Deep Learning algorithms, which typically …
detecting objects in images and videos. Unlike Deep Learning algorithms, which typically …
An evaluation of synthetic data augmentation for mitigating covariate bias in health data
Data bias is a major concern in biomedical research, especially when evaluating large-scale
observational datasets. It leads to imprecise predictions and inconsistent estimates in …
observational datasets. It leads to imprecise predictions and inconsistent estimates in …
[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 …
Synthetic census microdata generation: A comparative study of synthesis methods examining the trade-off between disclosure risk and utility
There is growing interest in synthetic data generation as a means of allowing access to
useful data whilst preserving confidentiality. In particular, synthetic microdata generation …
useful data whilst preserving confidentiality. In particular, synthetic microdata generation …
[HTML][HTML] Advancing student outcome predictions through generative adversarial networks
Predicting student outcomes is essential in educational analytics for creating personalised
learning experiences. The effectiveness of these predictive models relies on having access …
learning experiences. The effectiveness of these predictive models relies on having access …
Convex space learning for tabular synthetic data generation
Generating synthetic samples from the convex space of the minority class is a popular
oversampling approach for imbalanced classification problems. Recently, deep-learning …
oversampling approach for imbalanced classification problems. Recently, deep-learning …