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Datasets:
Peng-AI
/
hescape-pyarrow

Tasks:
Image Classification
Feature Extraction
Image Segmentation
Modalities:
Image
Text
Formats:
parquet
Languages:
English
Size:
100K - 1M
ArXiv:
Tags:
spatial-transcriptomics
histology
pathology
benchmark
Libraries:
Datasets
Dask
License:
Dataset card Data Studio Files
xet
Community
1

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  • This dataset and associated code are released under the CC-BY-NC-ND 4.0 license and may only be used for non-commercial, academic research purposes with proper attribution. - Any commercial use, sale, or other monetization of the hescape dataset and its derivatives, which include models trained on outputs from the hescape datasets, is prohibited and requires prior approval. - By downloading the dataset, you attest that all information (affiliation, research use) is correct and up-to-date. Downloading the dataset requires prior registration on Hugging Face and agreeing to the terms of use. By downloading this dataset, you agree not to distribute, publish or reproduce a copy of the dataset. If another user within your organization wishes to use the hescape dataset, they must register as an individual user and agree to comply with the terms of use. Users may not attempt to re-identify the deidentified data used to develop the underlying dataset.
  • This dataset is provided “as-is” without warranties of any kind, express or implied. This dataset has not been reviewed, certified, or approved by any regulatory body, including but not limited to the FDA (U.S.), EMA (Europe), MHRA (UK), or other medical device authorities. Any application of this dataset in healthcare or biomedical settings must comply with relevant regulatory requirements and undergo independent validation. Users assume full responsibility for how they use this dataset and any resulting consequences. The authors, contributors, and distributors disclaim any liability for damages, direct or indirect, resulting from dataset use. Users are responsible for ensuring compliance with data protection regulations (e.g., GDPR, HIPAA) when using it in research that involves patient data.

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