Implicit knowledge learning:taking clinical simulation for example

Jun DONG

doi:10.11959/j.issn.2096-6652.202149

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Implicit knowledge learning:taking clinical simulation for example

Papers and Reports | 更新时间：2024-06-05

- Implicit knowledge learning:taking clinical simulation for example
- Chinese Journal of Intelligent Science and Technology Vol. 3, Issue 4, Pages: 492-498(2021)
- 作者机构：
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- DOI：10.11959/j.issn.2096-6652.202149
  CLC： TP391
- Published Online：2021-12，
  
  Published：15 December 2021
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Jun DONG. Implicit knowledge learning:taking clinical simulation for example[J]. Chinese journal of intelligent science and technology, 2021, 3(4): 492-498.
DOI：

Jun DONG. Implicit knowledge learning:taking clinical simulation for example[J]. Chinese journal of intelligent science and technology, 2021, 3(4): 492-498. DOI： 10.11959/j.issn.2096-6652.202149.

摘要

在计算机辅助心血管疾病诊断研究过程中，已有方法大多忽视领域经验的全面建模，针对此问题提出关注隐性知识的挖掘与学习策略。讨论了知识工程中隐性知识的重要性及其向显式知识转化的过程，介绍了模拟医生专家思维过程的规则推理与机器学习相结合的技术路线，分析了计算机辅助中医新方生成理念，即机器通过模拟中医思维过程给出针对某种疾病的全新处方。希望本思想能为人工智能其他领域的应用建模提供参考。

Abstract

In the course of computer-aided cardiovascular disease diagnosis

field experience modeling usually being ignored.Hereafter the strategy to focus on the discovey and study of implicit knowledge was presented.The importance of implicit knowledge in knowledge engineering and its transformation process to explicit knowledge was discussed.Technical roadmap simulating physicians’ thinking by infusing rules inference and machine learning was introduced.And the computer-aided traditional Chinese medicine new prescription generating was analysed

that is

the machine gave a new prescription for a certain disease by simulating the thinking process of traditional Chinese medicine.It is hoped that this approach can provide a reference for the modeling of applications in other fields of artificial intelligence.

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references

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