In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 12

Research on electronic health record data generation for diffusion models

Wei Bolun1
Zhang Xiankun1
1. School of Artificial Intelligence, Tianjin University of Science & Technology, Tianjin 300457, China
DOI: 10.19734/j.issn.1001-3695.2024.04.0122

Abstract

Electronic Health Records (EHR) data in the medical field contain a wealth of valuable biomedical knowledge and provide a crucial resource for healthcare data analysis. However, privacy protection and data sharing constraints have become significant bottlenecks for researchers, hindering the application and development of data analysis and machine learning techniques in healthcare. To address these challenges, researchers have been exploring the use of generative modeling methods to generate EHR data. This paper aims to systematically review the development of diffusion models within generative models and their application in the field of EHR data generation. Firstly, we introduce and summarize the origins and evolution of diffusion models. Next, we delve into various existing diffusion model methods, providing a detailed analysis of each approach. We then list and compare different generative modeling methods applied in EHR data generation, emphasizing the advantages and limitations of diffusion models. Finally, we summarize the current applications of diffusion models in EHR data generation, discuss the limitations of current research, and present an outlook on the future development and application of diffusion models in this field.

Foundation Support

国家自然科学基金资助项目(62377036)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.04.0122
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 12

Publish History

[2024-09-02] Accepted Paper

Cite This Article

魏博伦, 张贤坤. 面向扩散模型的电子健康档案数据生成研究综述 [J]. 计算机应用研究, 2024, 41 (12). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.04.0122. (Wei Bolun, Zhang Xiankun. Research on electronic health record data generation for diffusion models [J]. Application Research of Computers, 2024, 41 (12). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.04.0122. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)