Data augmentation using llms: Data perspectives, learning paradigms and challenges
In the rapidly evolving field of large language models (LLMs), data augmentation (DA) has
emerged as a pivotal technique for enhancing model performance by diversifying training …
emerged as a pivotal technique for enhancing model performance by diversifying training …
A survey of generative adversarial networks for synthesizing structured electronic health records
Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and
point of care applications; however, many challenges such as data privacy concerns impede …
point of care applications; however, many challenges such as data privacy concerns impede …
A comprehensive survey on generative diffusion models for structured data
In recent years, generative diffusion models have achieved a rapid paradigm shift in deep
generative models by showing groundbreaking performance across various applications …
generative models by showing groundbreaking performance across various applications …
A survey on diffusion models for time series and spatio-temporal data
The study of time series data is crucial for understanding trends and anomalies over time,
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …
Guided discrete diffusion for electronic health record generation
Electronic health records (EHRs) are a pivotal data source that enables numerous
applications in computational medicine, eg, disease progression prediction, clinical trial …
applications in computational medicine, eg, disease progression prediction, clinical trial …
Fast and reliable generation of ehr time series via diffusion models
Electronic Health Records (EHRs) are rich sources of patient-level data, including laboratory
tests, medications, and diagnoses, offering valuable resources for medical data analysis …
tests, medications, and diagnoses, offering valuable resources for medical data analysis …
面向扩散模型的电子健康档案数据生成研究综述.
魏博伦， 张贤坤 - Application Research of Computers …, 2024 - search.ebscohost.com
医学领域的电子健康档案(electronichealthrecords, EHR) 数据涵盖了大量宝贵的生物医学知识,
为医疗数据分析提供了重要的资源. 然而, 隐私保护和数据共享的限制成为研究的主要瓶颈 …
为医疗数据分析提供了重要的资源. 然而, 隐私保护和数据共享的限制成为研究的主要瓶颈 …
A Survey on Generative Diffusion Models for Structured Data
H Koo - arXiv preprint arXiv:2306.04139, 2023 - arxiv.org
In recent years, generative diffusion models have achieved a rapid paradigm shift in deep
generative models by showing groundbreaking performance across various applications …
generative models by showing groundbreaking performance across various applications …
SynSUM--Synthetic Benchmark with Structured and Unstructured Medical Records
We present the SynSUM benchmark, a synthetic dataset linking unstructured clinical notes
to structured background variables. The dataset consists of 10,000 artificial patient records …
to structured background variables. The dataset consists of 10,000 artificial patient records …
Fast Sampling via De-randomization for Discrete Diffusion Models
Diffusion models have emerged as powerful tools for high-quality data generation, such as
image generation. Despite its success in continuous spaces, discrete diffusion models …
image generation. Despite its success in continuous spaces, discrete diffusion models …