HoneyBee
Collection
A collection of public multimodal oncology datasets generated using the HoneyBee framework.
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pdf
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HoneyBee Sample Files
Sample data for the HoneyBee framework — a scalable, modular toolkit for multimodal AI in oncology.
These files are used by the HoneyBee example notebooks to demonstrate clinical, pathology, and radiology processing pipelines.
Paper: HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology Datasets with Foundational Embedding Models
Package: pip install honeybee-ml
Files
| File | Type | Size | Description |
|---|---|---|---|
sample.PDF |
Clinical | 70 KB | De-identified clinical report (PDF) for NLP extraction |
sample.svs |
Pathology | 146 MB | Whole-slide image (Aperio SVS) for tissue detection, patch extraction, and embedding |
CT/ |
Radiology | 105 MB | CT scan with 2 DICOM series (205 slices total) for radiology preprocessing |
CT Directory Structure
CT/
├── 1.3.6.1.4.1.14519.5.2.1.6450.4007.1209.../ (101 slices)
└── 1.3.6.1.4.1.14519.5.2.1.6450.4007.2906.../ (104 slices)
Citation
Tripathi, A., Waqas, A., Schabath, M.B. et al. HONeYBEE: enabling scalable multimodal AI in
oncology through foundation model-driven embeddings. npj Digit. Med. 8, 622 (2025).
https://doi.org/10.1038/s41746-025-02003-4
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