This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1367) Big Data (286) Methods and Instruments in Medical Informatics (167) New Technologies (96) Research Infrastructures and Registries (73) Tools, Programs and Algorithms (326) Data Science (314)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55118, first published .
Comparison of Synthetic Data Generation Techniques for Control Group Survival Data in Oncology Clinical Trials: Simulation Study

Comparison of Synthetic Data Generation Techniques for Control Group Survival Data in Oncology Clinical Trials: Simulation Study

Comparison of Synthetic Data Generation Techniques for Control Group Survival Data in Oncology Clinical Trials: Simulation Study

Authors of this article:

Ippei Akiya1 Author Orcid Image ;   Takuma Ishihara2 Author Orcid Image ;   Keiichi Yamamoto3 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

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  2. El Kababji S, Mitsakakis N, Jonker E, Beltran-Bless A, Pond G, Vandermeer L, Radhakrishnan D, Mosquera L, Paterson A, Shepherd L, Chen B, Barlow W, Gralow J, Savard M, Fesl C, Hlauschek D, Balic M, Rinnerthaler G, Greil R, Gnant M, Clemons M, El Emam K. Augmenting Insufficiently Accruing Oncology Clinical Trials Using Generative Models: Validation Study. Journal of Medical Internet Research 2025;27:e66821 View
  3. Mishra H, Gupta R. Leveraging Generative AI for Drug Safety and Pharmacovigilance. Current Reviews in Clinical and Experimental Pharmacology 2025;20(2):89 View