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Foundations of Medical Large Language Model Learning
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| 2026-07-31 | 1795 |
| 2026-08-03 | 1835 |
| 2026-08-06 | 1835 |
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<h1 align="center">医疗大模型基础</h1>
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本书旨在为对医疗大模型感兴趣的读者系统地讲解相关基础知识、介绍前沿技术。作者团队将认真听取开源社区以及广大专家学者的建议，持续进行**月度更新**，致力打造**易读、严谨、有深度**的医疗大模型教材。并且，本书还将针对每章内容配备相关的**Paper List**，以跟踪相关技术的**最新进展**。
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本书第一版包括**从人工智能到医疗大模型**、**医疗大模型的技术基石**、**从通用领域到医疗垂直领域**、**前沿临床与科研应用**、**挑战、伦理与未来**等五部分。当前版本所含内容均来源于作者团队对相关方向的探索与理解，如有谬误，恳请大家多提issue，多多赐教。
其中每个章节的内容目录如下表所示。
## 本书目录
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<th style="text-align:center; width: 25%;">章节</th>
<th style="text-align:center; width: 75%;" colspan="4">所含内容</th>
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<td rowspan="1"><b><a href="https://github.com/ZJU-LLMs/Foundations-of-Medical-LLMs">第一部分：从人工智能到医疗大模型</a></b></td>
<td style="width: 25%;"><a href="content/chapter1.pdf">1 医疗人工智能的演进史</a></td>
<td style="width: 25%;"><a href="content/chapter2.pdf">2 大语言模型（LLM）初探</a></td>
<td style="width: 25%;"><a href="content/chapter3.pdf">3 当医疗遇上大模型</a></td>
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<td rowspan="1"><b><a href="https://github.com/ZJU-LLMs/Foundations-of-Medical-LLMs">第二部分 ：医疗大模型的技术基石</a></b></td>
<td style="width: 25%;"><a href="content/chapter4.pdf">4 大模型的心脏：Transformer架构</a></td>
<td style="width: 25%;"><a href="content/chapter5.pdf">5 大模型的炼丹术：预训练与微调</a></td>
<td style="width: 25%;"><a href="content/chapter6.pdf">6 让大模型更聪明：提示词工程与外挂大脑</a></td>
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<td rowspan="1"><b><a href="https://github.com/ZJU-LLMs/Foundations-of-Medical-LLMs">第三部分：从通用领域到医疗垂直领域</a></b></td>
<td style="width: 25%;"><a href="content/chapter-7.pdf">7 医疗数据的金矿与炼金术</td>
<td style="width: 25%;"><a href="content/chapter-8.pdf">8 医疗大模型的垂直化训练策略</td>
<td style="width: 25%;"><a href="content/chapter-9.pdf">9 医疗大模型前沿技术 </td>
<td style="width: 25%;"><a href="content/chapter-10.pdf">10 医疗大模型的评测与基准</td>
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<td rowspan="1"><b><a href="https://github.com/ZJU-LLMs/Foundations-of-Medical-LLMs">第四部分：前沿临床与科研应用</a></b></td>
<td style="width: 25%;"><a href="content/chapter 11.pdf">11 临床决策支持系统（CDSS）的智能化跃迁</td>
<td style="width: 25%;"><a href="content/chapter 12.pdf">12 医疗文书自动化与环境临床智能（ACI）</td>
<td style="width: 25%;"><a href="content/chapter 13.pdf">13 患者体验重塑：全生命周期的智能管家</td>
<td style="width: 25%;"><a href="content/chapter 13.pdf">14 生命科学前沿：大模型加速新药研发</td>
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<td rowspan="1"><b><a href="https://github.com/ZJU-LLMs/Foundations-of-Medical-LLMs">第五部分：挑战、伦理与未来</a></b></td>
<td style="width: 25%;"><a href="content/chapter-15.pdf">15 悬在头顶的达摩克利斯之剑：机器幻觉（Hallucinations）</a></td>
<td style="width: 25%;"><a href="content/chapter-16.pdf">16 数据隐私、安全与合规</a></td>
<td style="width: 25%;"><a href="content/chapter-17.pdf">17 医学伦理与算法偏见</a></td>
<td style="width: 25%;"><a href="content/chapter-18.pdf">18 未来展望：多模态与医疗AGI</a></td>
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## 致谢
本书的不断优化，将仰仗各位读者的帮助与支持。您的建议将成为我们持续向前的动力！
如果有此书相关的其他问题，请随时联系我们，可发送邮件至：[email protected]。
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:254f80bc7c453218, llm:Repository name and description: 'Foundations of Medical Large Language Model Learning' — indicates focus on medical LLMs (foundations, learning). No topics or README provided.
matched fp:254f80bc7c453218, llm:Repository name and description: 'Foundations of Medical Large Language Model Learning' — indicates focus on medical LLMs (foundations, learning). No topics or README provided.
matched fp:254f80bc7c453218, llm:Repository name and description: 'Foundations of Medical Large Language Model Learning' — indicates focus on medical LLMs (foundations, learning). No topics or README provided.
matched fp:254f80bc7c453218, llm:Repository name and description: 'Foundations of Medical Large Language Model Learning' — indicates focus on medical LLMs (foundations, learning). No topics or README provided.