Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46725, first published .
A Pragmatic Method to Integrate Data From Preexisting Cohort Studies Using the Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model: Case Study

A Pragmatic Method to Integrate Data From Preexisting Cohort Studies Using the Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model: Case Study

A Pragmatic Method to Integrate Data From Preexisting Cohort Studies Using the Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model: Case Study

Journals

  1. Pigeot I, Ahrens W, Darms J, Fluck J, Golebiewski M, Hahn H, Hu X, Intemann T, Kasbohm E, Kirsten T, Klammt S, Klopfenstein S, Lassen-Schmidt B, Peters M, Sax U, Waltemath D, Schmidt C. Making Epidemiological and Clinical Studies FAIR Using the Example of COVID-19. Datenbank-Spektrum 2024;24(2):117 View
  2. Bejerano-Blázquez I, Familiar-Cabero M. On the Application of Artificial Intelligence and Cloud-Native Computing to Clinical Research Information Systems: A Systematic Literature Review. Information 2025;16(8):684 View
  3. Sun C, Ling G, Sun C, Feng X. Evaluation of the efficacy of Yiqi Jiedu decoction on diabetic peripheral neuropathy and related brain function changes: A randomized controlled trial protocol. European Journal of Integrative Medicine 2025;78:102543 View

Books/Policy Documents

  1. Kazi J. Python Essentials for Biomedical Data Analysis: An Introductory Textbook. View

Conference Proceedings

  1. Wu J, Zuo Q, Pan H, Li P. 2025 IEEE International conference on Medical Artificial Intelligence (MedAI). Advancements in Automated Methods for Research Data Extraction and Integration from Electronic Health Records View