Lab-Rasool/honeybee-samples
HoneyBee Sample Files Sample data and resource files for the HoneyBee framework — a scalable, modular toolkit for multimodal AI in oncology. These files are used by the HoneyBee example notebooks (clinical, pathology, radiology) and by HoneyBee's molecular processing code at runtime (Hugo_symbols.tsv is fetched on first use of DNA mutation preprocessing). Paper: HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology Datasets with Foundational Embedding Models… See the full description on the dataset page: https://huggingface.co/datasets/Lab-Rasool/honeybee-samples.
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1---2task_categories:3 - image-classification4 - feature-extraction5tags:6 - medical7 - pathology8 - radiology9 - clinical10 - molecular11 - multi-omics12 - oncology13 - whole-slide-image14 - dicom15 - multimodal16size_categories:17 - n<1K18pretty_name: HoneyBee Sample Files19---20 21# HoneyBee Sample Files22 23Sample data and resource files for the [HoneyBee](https://github.com/Lab-Rasool/HoneyBee) framework — a scalable, modular toolkit for multimodal AI in oncology.24 25These files are used by the HoneyBee example notebooks (clinical, pathology, radiology) and by HoneyBee's molecular processing code at runtime (`Hugo_symbols.tsv` is fetched on first use of DNA mutation preprocessing).26 27**Paper**: [HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology Datasets with Foundational Embedding Models](https://arxiv.org/abs/2405.07460)28**Package**: [`pip install honeybee-ml`](https://pypi.org/project/honeybee-ml/)29 30## Files31 32| File | Type | Size | Description |33|------|------|------|-------------|34| `sample.PDF` | Clinical | 70 KB | De-identified clinical report (PDF) for NLP extraction |35| `sample.svs` | Pathology | 146 MB | Whole-slide image (Aperio SVS) for tissue detection, patch extraction, and embedding |36| `CT/` | Radiology | 105 MB | CT scan with 2 DICOM series (205 slices total) for radiology preprocessing |37| `Hugo_symbols.tsv` | Molecular | 128 KB | Hugo Gene Symbol vocabulary (17,312 symbols, one per line, no header) used by SeNMo's DNA mutation preprocessing. Ported from [lab-rasool/SeNMo](https://github.com/lab-rasool/SeNMo). Fetched automatically by `honeybee.processors.molecular.preprocessing.preprocess_dna_mutation()` on first use. |38 39### CT Directory Structure40 41```42CT/43├── 1.3.6.1.4.1.14519.5.2.1.6450.4007.1209.../ (101 slices)44└── 1.3.6.1.4.1.14519.5.2.1.6450.4007.2906.../ (104 slices)45```46 47## Citation48 49```bibtex50Tripathi, A., Waqas, A., Schabath, M.B. et al. HONeYBEE: enabling scalable multimodal AI in51oncology through foundation model-driven embeddings. npj Digit. Med. 8, 622 (2025).52https://doi.org/10.1038/s41746-025-02003-453```54 55If your work uses `Hugo_symbols.tsv` (the molecular sample), also cite the SeNMo paper that originally curated this vocabulary:56 57```bibtex58Waqas, A., Tripathi, A., Ahmed, S. et al. Self-Normalizing Multi-Omics Neural Network for59Pan-Cancer Prognostication. Int. J. Mol. Sci. 26, 7358 (2025).60https://doi.org/10.3390/ijms2615735861```