HONeYBEE: enabling scalable multimodal AI in oncology through foundation model-driven embeddings
9.5
来源：
Nature
关键字：
AI brain science
发布时间：
2025-10-23 15:31
摘要：
HONeYBEE (Harmonized ONcologY Biomedical Embedding Encoder) is an open-source framework designed to integrate multimodal biomedical data for oncology applications. It processes clinical data, imaging, and molecular profiles to generate unified patient-level embeddings, achieving high accuracy in cancer classification and survival prediction. Evaluated on a large dataset from The Cancer Genome Atlas (TCGA), HONeYBEE demonstrates its potential to enhance predictive modeling in oncology, making it a valuable tool for researchers and clinicians in precision medicine.
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关键证据
HONeYBEE achieved 98.5% classification accuracy and 96.4% precision in patient retrieval.
The framework integrates clinical, imaging, and molecular data to enhance predictive performance.
Evaluated on over 11,400 patients across 33 cancer types, demonstrating its robustness.
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AI评分总结
HONeYBEE (Harmonized ONcologY Biomedical Embedding Encoder) is an open-source framework designed to integrate multimodal biomedical data for oncology applications. It processes clinical data, imaging, and molecular profiles to generate unified patient-level embeddings, achieving high accuracy in cancer classification and survival prediction. Evaluated on a large dataset from The Cancer Genome Atlas (TCGA), HONeYBEE demonstrates its potential to enhance predictive modeling in oncology, making it a valuable tool for researchers and clinicians in precision medicine.