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🧬 BioReason: биомедицинская нейросеть, которая реально *думает*
От лаборатории Bo Wang (U of Toronto)

BioReason — это reasoning-модель для биомедицинских задач, которая учится делать *глубокие логические выводы* по статьям, графам знаний и научным данным.
💡 Не просто "угадывает", а *обобщает и объясняет*.

📚 Обучена на:
• PubMed abstracts
• PICO фреймах
• SNOMED CT и других онтологиях
• Biomedical Knowledge Graphs

🚀 Особенности:
• Архитектура на основе LM+GNN+reasoning engine
• Сильна в задачах like QA, classification, relation extraction
• Поддержка chain-of-thought + multi-hop inference
• Основана на OpenPretrain и GALACTICA

🧪 Benchmark’и:
+18–22% точности по сравнению с BioLinkBERT и GPT-3.5 на ряде задач (MedQA, PubMedQA, MedNLI и др.)

# Clone the repository
git clone https://github.com/bowang-lab/BioReason.git
cd BioReason

# Install package
pip install -e .

🔗 GitHub: https://github.com/bowang-lab/BioReason
📄 Статья: https://arxiv.org/abs/2406.02491

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3.5K viewsJun 16 at 07:55

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Create: 2025-06-16
Last Update: 2025-06-19 13:02:50

🧬 BioReason: биомедицинская нейросеть, которая реально *думает*
От лаборатории Bo Wang (U of Toronto)

BioReason — это reasoning-модель для биомедицинских задач, которая учится делать *глубокие логические выводы* по статьям, графам знаний и научным данным.
💡 Не просто "угадывает", а *обобщает и объясняет*.

📚 Обучена на:
• PubMed abstracts
• PICO фреймах
• SNOMED CT и других онтологиях
• Biomedical Knowledge Graphs

🚀 Особенности:
• Архитектура на основе LM+GNN+reasoning engine
• Сильна в задачах like QA, classification, relation extraction
• Поддержка chain-of-thought + multi-hop inference
• Основана на OpenPretrain и GALACTICA

🧪 Benchmark’и:
+18–22% точности по сравнению с BioLinkBERT и GPT-3.5 на ряде задач (MedQA, PubMedQA, MedNLI и др.)

# Clone the repository
git clone https://github.com/bowang-lab/BioReason.git
cd BioReason

# Install package
pip install -e .

🔗 GitHub: https://github.com/bowang-lab/BioReason
📄 Статья: https://arxiv.org/abs/2406.02491

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Date: 2025-06-19|

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