Large language model trained on clinical oncology data predicts cancer progression
Abstract Subspecialty knowledge barriers have limited the adoption of large language models (LLMs) in oncology. We introduce Woollie, an open-source, oncology-specific LLM trained on real-world data from Memorial Sloan Kettering Cancer Center (MSK) across lung, breast, prostate, pancreatic, and colo...
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| Main Authors: | Menglei Zhu, Hui Lin, Jue Jiang, Abbas J. Jinia, Justin Jee, Karl Pichotta, Michele Waters, Doori Rose, Nikolaus Schultz, Sulov Chalise, Lohit Valleru, Olivier Morin, Jean Moran, Joseph O. Deasy, Shirin Pilai, Chelsea Nichols, Gregory Riely, Lior Z. Braunstein, Anyi Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01780-2 |
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