Enhanced Conditional GAN for High-Quality Synthetic Tabular Data Generation in Mobile-Based Cardiovascular Healthcare

The generation of synthetic tabular data has emerged as a critical task in various fields, particularly in healthcare, where data privacy concerns limit the availability of real datasets for research and analysis. This paper presents an enhanced Conditional Generative Adversarial Network (GAN) archi...

Full description

Saved in:

Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 24; no. 23; p. 7673
Main Authors:	Alqulaity, Malak, Yang, Po
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 01.12.2024 MDPI
Subjects:	Algorithms Artificial intelligence Cardiovascular disease Cardiovascular Diseases Cardiovascular research Comparative analysis Datasets Delivery of Health Care Electronic data processing Electronic health records generative adversarial networks Health informatics Humans Machine learning machine learning in healthcare medical informatics Medical research Methods Neural networks Neural Networks, Computer synthetic data generation tabular data Technology application Telemedicine United Kingdom generative adversarial networks cardiovascular disease machine learning in healthcare medical informatics synthetic data generation tabular data
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!