隐性知识学习——以临床模拟为例

doi:10.11959/j.issn.2096-6652.202149

Abstract

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.

Key words: intelligence simulation, implicit knowledge, experience, common sense, computer-aided diagnosis

CLC Number:

TP391

Jun DONG. Implicit knowledge learning:taking clinical simulation for example[J]. Chinese Journal of Intelligent Science and Technology, 2021, 3(4): 492-498.

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[8]	DONG J . Engineering-oriented study on modernization of traditional Chinese medicine—taking innovative prescription as an example[J]. Science, 2021,73(3): 33-35.
[9]	董军 . 辩证中医[J]. 科学, 2020,72(4): 39-42.
	DONG J . Traditional Chinese medicine and challenge of the times[J]. Science, 2020,72(4): 39-42.
[10]	董军 . 中医切脉模拟之困境[J]. 科学, 2017,69(4): 34-36.
	DONG J . The predicament on simulation of Chinese traditional pulse-taking[J]. Science, 2017,69(4): 34-36.
[11]	叶永烈 . 华丽转身[M]. 成都: 天地出版社, 2017:590.
	YE Y L . Turing around gorgeously[M]. Chengdu: Tiandi Press, 2017:590.
[12]	JIN L P , DONG J . Intelligent health vessel ABC-DE:an electrocardiogram cloud computing service[J]. IEEE Transactions on Cloud Computing, 2020,8(3): 861-874.
[1]	阿尔伯特·爱因斯坦 . 爱因斯坦文集（第一卷）[M]. 北京: 商务印书馆, 1976:445.
	EINSTEIN A . The collected works of Einstein (volumeⅠ)[M]. Beijing: The Commercial Press, 2009:445.
[2]	克利福德·格尔茨 . 地方知识——阐释人类学论文集[M]. 杨德睿,译.北京: 商务印书馆, 2014:123,145.
	GEERTZ C . Local knowledge:further essays in interpretive anthropology[M]. Translated by YANG D R. Beijing: The Commercial Press,, 2014:123,145.
[3]	迈克尔.波兰尼 . 个人知识[M]. 许泽民,译.贵阳: 贵州人民出版社, 2000:152.
	POLANYI M . Personal knowledge[M]. Translated by XU Z M. Guiyang: Guizhou People’s Publishing House Co.,Ltd., 2000:152.
[4]	DONG J , ZHANG J W , ZHU H H ,et al. A remote diagnosis service platform for wearable ECG monitors[J]. IEEE Intelligent Systems, 2012,27(6): 36-43.
[5]	董军 . “心迹”的计算——隐性知识的人工智能途径[M]. 上海: 上海科学技术出版社, 2017.
	DONG J . Computation of heart ＆ mind trace:artificial intelligence approach on implicit knowledge[M]. Shanghai: Shanghai Scientific and tecnnical Press, 2017.
[6]	ZHOU F Y , JIN L P , DONG J . Premature ventricular contraction detection combining deep neural networks and rules inference[J]. Artificial Intelligence in Medicine, 2017,79: 42-51.
[7]	约翰.杜威 . 确定性的寻求:关于知行关系的研究[M]. 傅统先,译.上海: 上海人民出版社, 2005:160.
	DEWEY J . The quest for certainty:a study of the relation of knowledge and action[M]. Translated by FU T X. Shanghai: Shangha People’s Publishing House, 2005:160.
[8]	董军 . 面向工程的中医现代化探索:以新方生成为例[J]. 科学, 2021,73(3): 33-35.

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