人工智能——引领中医学新发展的有效工具
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摘要
伴随AlphaGo Zero称霸围棋领域,谷歌公司宣布全力转向智慧医疗方向发展,深度学习训练虚拟老鼠可以模拟人类大脑空间导航能力的飞跃式进展,全球医疗领域的人工智能技术进入了高速发展阶段。人工智能为西医的体外诊断技术、手术导航等方面提供了极大帮助,也通过专家系统、大数据、辅助诊断设备等方面协助中医诊断,规范中医诊疗。
With AlphaGo Zero dominating the field of chess, Google has announced that it has turned to the development of smart healthcare. With the training by deep learning, virtual mice can simulate the leap-forward progress of human brain space navigation capabilities. Thus, the global artificial intelligence technology in the medical field has entered a period of rapid development. Artificial intelligence has provided great help for western medical imaging technology, in vitro diagnostic technology, surgical navigation, etc. It has also assisted in the diagnosis of traditional Chinese medicine through expert systems, big data, and auxiliary diagnostic equipment, and standardized Chinese medicine diagnosis and treatment.
With AlphaGo Zero dominating the field of chess, Google has announced that it has turned to the development of smart healthcare. With the training by deep learning, virtual mice can simulate the leap-forward progress of human brain space navigation capabilities. Thus, the global artificial intelligence technology in the medical field has entered a period of rapid development. Artificial intelligence has provided great help for western medical imaging technology, in vitro diagnostic technology, surgical navigation, etc. It has also assisted in the diagnosis of traditional Chinese medicine through expert systems, big data, and auxiliary diagnostic equipment, and standardized Chinese medicine diagnosis and treatment.
引文
1张德政,哈爽,刘欣,等.中医药领域人工智能的研究与发展.情报工程, 2018, 4(1):13-23.
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4 Adlassnig K P. Artificial-intelligence-augmented systems. Artificial Intelligence in Medicine, 2002, 24(1):1-4.
5 杨琴,陈家荣.人工智能在医学领域中的应用.科技风, 2012(12):100-101.
6 伍欣.中医诊疗专家辅助系统的研究与实现.绵阳:西南科技大学,2006.
7 李海鲲,胡存刚,宗仁鹤.基于数据库的中医专家诊断系统的研究.微处理机, 2005, 26(1):26-28.
8 李庆利,薛永祺,刘治.基于高光谱成像技术的中医舌象辅助诊断系统.生物医学工程学杂志, 2008, 25(2):368-371.
9 孙炀,罗瑜,周昌乐,等.一种基于分裂-合并方法的中医舌像区域分割算法及其实现.中国图象图形学报, 2003, 8(12):1395-1399.
10 Chung Y F, Hu C S, Luo C H, et al. Possibility of quantifying TCM finger-reading sensations:II. an example of health standardization. Eur J Integr Med, 2012, 4(3):e263.
11 Kahn C E. From images to actions:opportunities for artificial intelligence in radiology. Radiology, 2017, 285:719-720.
12 2018-2024年中国人工智能+医疗影像行业市场研究及投资前景预测报告. http://www. chyxx. com/research/201710/578114. html.
13 Gulshan V, Peng L, Coram M, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA, 2016, 316:2402-2410.
14 Le Cun Y, Bengio Y, Hinton G. Deep learning. Nature, 2015, 521:436-444.
15 Andre E, Brett K, Roberto A N, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature, 2017, 542:115-118.
16 Long E, Lin H, Liu Z, et al. An artificial intelligence platform for the multihospital collaborative management of congenital cataracts. Nature Biomedical Engineering, 2017, 1:0024.
17 Hayato T, Shuichi H, Munekazu N, et al. Specific autoantigens identified by sera obtained from mice that are immunized with testicular germ cells alone. Nature, 2016:1-16.
18 Andrea B, Caswell B, Benigno U, et al. Vector-based navigation using grid-like representations in artificial agents. Nature, 2018, 557(7705):429-433.
19 Fedorov A V, Kriger A G, Berelavichus S V, et al. Robotic-assisted abdominal surgery. Khirurgiia(Mosk), 2010,(1):16-21.
20 吉翔,于建平,石鑫,等.全机器人下远端胃癌根治术的近期疗效.华南国防医学杂志, 2018, 32(2):91-93.
21 杨阳,赵晓智,姚林方,等.机器人辅助腹腔镜下射频消融术治疗肾肿瘤的临床观察.临床泌尿外科杂志, 2018, 33(2):152-159.
22 史博文,孙冰生,岳东升,等.达芬奇手术系统与胸腔镜在肺癌根治术中的对比分析.肿瘤防治研究, 2018, 45(2):91-95.
23 贝太学,王涛,乔建滨.基于中医专家系统的评价技术综述.信息技术与信息化, 2011, 1:52-55.
24 王映辉,张润顺,吴洁,等.名老中医经验传承研究模式探索.中国中医基础医学杂志, 2008, 6:417-418.
25 张玉,肖勇,赵娜.名老中医专家门诊病案管理信息系统构建关键问题探讨.湖北中医杂志, 2015, 37(9):72-73.
26 张润顺,王映辉,周雪忠,等.名老中医经验要素研究及智能挖掘平台功能设计.世界科学技术-中医药现代化, 2008, 1:45-52+63.
27 Kim J, Son J, Jang S, et al. Availability of tongue diagnosis system for assessing tongue coating thickness in patients with functional dyspepsia.Evid-based Compl Alt, 2013, 2013(6):348-272.
28 蒋颖,刘聪颖,张亚丹,等.脉诊检测分析仪的研究进展与新思路.中华中医药杂志, 2017, 32(1):218-221.
29 李洋,陈小惠.便携式多生理参数网络化监测研究与设计.计算机技术与发展, 2015, 25(10):187-190.
30 刘景陶,柳耀花.计算机分子模拟技术及人工智能在药物研发中的应用.科技创新与应用, 2018, 2:46-47.
2 Coles L S. The application of artificial intelligence to medicine. Futures,1977:315-323.
3 Niels P, Carlo C, Roque M, et al. Thirty years of artificial intelligence in medicine(AIME)conferences:a review of research themes. Artificial Intelligence in Medicine, 2015, 65:61-73.
4 Adlassnig K P. Artificial-intelligence-augmented systems. Artificial Intelligence in Medicine, 2002, 24(1):1-4.
5 杨琴,陈家荣.人工智能在医学领域中的应用.科技风, 2012(12):100-101.
6 伍欣.中医诊疗专家辅助系统的研究与实现.绵阳:西南科技大学,2006.
7 李海鲲,胡存刚,宗仁鹤.基于数据库的中医专家诊断系统的研究.微处理机, 2005, 26(1):26-28.
8 李庆利,薛永祺,刘治.基于高光谱成像技术的中医舌象辅助诊断系统.生物医学工程学杂志, 2008, 25(2):368-371.
9 孙炀,罗瑜,周昌乐,等.一种基于分裂-合并方法的中医舌像区域分割算法及其实现.中国图象图形学报, 2003, 8(12):1395-1399.
10 Chung Y F, Hu C S, Luo C H, et al. Possibility of quantifying TCM finger-reading sensations:II. an example of health standardization. Eur J Integr Med, 2012, 4(3):e263.
11 Kahn C E. From images to actions:opportunities for artificial intelligence in radiology. Radiology, 2017, 285:719-720.
12 2018-2024年中国人工智能+医疗影像行业市场研究及投资前景预测报告. http://www. chyxx. com/research/201710/578114. html.
13 Gulshan V, Peng L, Coram M, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA, 2016, 316:2402-2410.
14 Le Cun Y, Bengio Y, Hinton G. Deep learning. Nature, 2015, 521:436-444.
15 Andre E, Brett K, Roberto A N, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature, 2017, 542:115-118.
16 Long E, Lin H, Liu Z, et al. An artificial intelligence platform for the multihospital collaborative management of congenital cataracts. Nature Biomedical Engineering, 2017, 1:0024.
17 Hayato T, Shuichi H, Munekazu N, et al. Specific autoantigens identified by sera obtained from mice that are immunized with testicular germ cells alone. Nature, 2016:1-16.
18 Andrea B, Caswell B, Benigno U, et al. Vector-based navigation using grid-like representations in artificial agents. Nature, 2018, 557(7705):429-433.
19 Fedorov A V, Kriger A G, Berelavichus S V, et al. Robotic-assisted abdominal surgery. Khirurgiia(Mosk), 2010,(1):16-21.
20 吉翔,于建平,石鑫,等.全机器人下远端胃癌根治术的近期疗效.华南国防医学杂志, 2018, 32(2):91-93.
21 杨阳,赵晓智,姚林方,等.机器人辅助腹腔镜下射频消融术治疗肾肿瘤的临床观察.临床泌尿外科杂志, 2018, 33(2):152-159.
22 史博文,孙冰生,岳东升,等.达芬奇手术系统与胸腔镜在肺癌根治术中的对比分析.肿瘤防治研究, 2018, 45(2):91-95.
23 贝太学,王涛,乔建滨.基于中医专家系统的评价技术综述.信息技术与信息化, 2011, 1:52-55.
24 王映辉,张润顺,吴洁,等.名老中医经验传承研究模式探索.中国中医基础医学杂志, 2008, 6:417-418.
25 张玉,肖勇,赵娜.名老中医专家门诊病案管理信息系统构建关键问题探讨.湖北中医杂志, 2015, 37(9):72-73.
26 张润顺,王映辉,周雪忠,等.名老中医经验要素研究及智能挖掘平台功能设计.世界科学技术-中医药现代化, 2008, 1:45-52+63.
27 Kim J, Son J, Jang S, et al. Availability of tongue diagnosis system for assessing tongue coating thickness in patients with functional dyspepsia.Evid-based Compl Alt, 2013, 2013(6):348-272.
28 蒋颖,刘聪颖,张亚丹,等.脉诊检测分析仪的研究进展与新思路.中华中医药杂志, 2017, 32(1):218-221.
29 李洋,陈小惠.便携式多生理参数网络化监测研究与设计.计算机技术与发展, 2015, 25(10):187-190.
30 刘景陶,柳耀花.计算机分子模拟技术及人工智能在药物研发中的应用.科技创新与应用, 2018, 2:46-47.