Published September 7, 2024
| Version v1
Dataset
Open
Studying Therapy Effects and Disease Outcomes in Silico using Artificial Counterfactual Tissue Samples
Authors/Creators
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1.
University Hospital Heidelberg
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2.
Universitätsklinikum Tübingen
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3.
University of Lucerne
Description
Counterfactual samples created by our generative method the CF-HistoGAN introduced in https://doi.org/10.48550/arXiv.2302.03120. This model was trained on and transformed data from 2 different datasets: the colorectal cancer (CRC) dataset by Schürch et al. https://doi.org/10.1016/j.cell. 2020.07.005 and the cutaneous T cell lymphoma (CTCL) by (Phillips et al https://doi.org/10.1038/s41467-021-26974-6.
Files
Files
(125.6 GB)
| Name | Size | Download all |
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md5:b50daebf220898dff0084572aaaea3b1
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43.2 GB | Download |
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md5:7714aabe4e8b46d0a4921fdacdf3ab8d
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40.6 GB | Download |
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md5:0d5a0bd92a41097e5cd5c255005d8558
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23.1 GB | Download |
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md5:306de5c699b509b87750bf42f260385a
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18.8 GB | Download |
Additional details
Identifiers
- arXiv
- arXiv:2302.03120
Related works
- Is part of
- Publication: arXiv:2302.03120 (arXiv)