HoneyBee Framework
A modular, open-source framework for multimodal oncology data processing and analysis
Key Features
Multimodal Data Integration
Process diverse oncology datasets: clinical notes, pathology slides, radiology scans, and molecular profiles.
Advanced Embeddings
Generate high-quality embeddings using domain-specific foundation models.
Clinical Data Processing
Extract structured information from clinical narratives and medical records.
Pathology Processing
Analyze whole slide images with stain normalization and tissue detection.
Radiology Processing
Process CT, MRI, and PET scans with specialized preprocessing techniques.
Molecular Analysis
Analyze DNA methylation, gene expression, protein expression, and more.
Framework Overview
HoneyBee is a modular, open-source framework that preprocesses diverse oncology datasets to generate consistent, high-quality embeddings using domain-specific foundation models.
The framework simplifies downstream applications such as prognosis estimation, cancer subtype classification, and retrieval-based tasks via a unified API.
HoneyBee enables reproducible and scalable machine learning workflows for precision oncology.
Ready to get started?
Explore the HoneyBee framework and start processing your multimodal oncology data today.