1.首都医科大学附属北京中医医院,北京市东城区美术馆后街23号,100010
2.北京市中医药研究所
3.北京中医药循证医学中心
4.北京中医药大学针灸推拿学院
5.北京交通大学计算机与信息技术学院
6.中华中医药学会
7.四川大学华西医院
libo@bjzhongyi.com
收稿:2022-05-03,
修回:2022-08-18,
纸质出版:2022-12-17
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赵国桢,郭诗琪,庞华鑫等.人工智能技术在辅助中医诊疗及诊疗标准化中的应用[J].中医杂志,2022,63(24):2306-2310.
ZHAO Guozhen,GUO Shiqi,PANG Huaxin,et al.Application of Artificial Intelligence in Assisting Diagnosis and Treatment in Traditional Chinese Medicine and Its Standardization[J].Journal of Traditional Chinese Medicine,2022,63(24):2306-2310.
赵国桢,郭诗琪,庞华鑫等.人工智能技术在辅助中医诊疗及诊疗标准化中的应用[J].中医杂志,2022,63(24):2306-2310. DOI: 10.13288/j.11-2166/r.2022.24.002.
ZHAO Guozhen,GUO Shiqi,PANG Huaxin,et al.Application of Artificial Intelligence in Assisting Diagnosis and Treatment in Traditional Chinese Medicine and Its Standardization[J].Journal of Traditional Chinese Medicine,2022,63(24):2306-2310. DOI: 10.13288/j.11-2166/r.2022.24.002.
中医诊疗标准化是中医药发展的重要保障,但以临床实践指南为核心的中医药标准化成果在临床应用时常面临困难,原因包括中医辨证论治主观性强、患者信息采集时缺少客观测量方法及客观指标、中医诊疗过程存在大量隐性知识等。基于人工智能技术的智能诊断系统和临床决策支持系统可为辅助中医诊疗及中医诊疗标准化工作提供新思路。一方面可借助中医智能诊断系统客观测量患者的中医四诊信息,辅助临床医生标准化诊断,推动中医诊断标准化的发展;另一方面能够建立症状群与药物群之间的网络关系,实现个体化治疗方案的推荐,促进中医治疗标准化的发展。建议未来人工智能技术应用于中医诊疗标准化研究中,应制定合适的结构化或半结构化病历,加强人工智能技术在数据采集中的应用,高效准确地采集患者信息;完善疗效评价体系,探索个体化疗效评价方法并评估人工智能技术的有效性和安全性;进一步探索符合中医诊疗特色的人工智能系统及数学模型。
As an important guarantee for the development of traditional Chinese medicine (TCM), the standardization of diagnosis and treatment is confronted with the difficulty of translating the achievements, such as the clinical practice guidelines, into the clinical use. The strong subjectivity of TCM syndrome differentiation and treatment, the lack of objective measurement methods and indicators when collecting patient information, and the existence of tacit knowledge in the TCM diagnosis and treatment process may explain the reasons. The intelligent diagnosis system and clinical decision support system based on artificial intelligence can provide new ideas and methods for assisting TCM diagnosis and treatment and its standardization. On one hand, with the help of the TCM intelligent diagnosis system, the information of the four examinations is measured objectively, assisting clinicians in standardized diagnosis and promoting the development of TCM diagnosis standardization. On the other hand, a network relationship between symptom groups and drug groups can be established to make the recommendation of individualized treatment plans, thereby promoting the development of standardization of TCM treatment. In future research on the combination of AI and TCM diagnosis and treatment standardization, firstly, appropriate structured or semi-structured medical records should be formulated, and the application of artificial intelligence in data collection should be strengthened, thereby collecting patient information efficiently and accurately. Secondly, we should improve the construction of the efficacy evaluation system, explore individualized efficacy evaluation methods, and evaluate the effectiveness and safety of AI technology. Finally, it is necessary to further explore AI systems and mathematical models suitable for the characteristics of TCM clinical diagnosis and treatment.
赵国桢 , 冯硕 , 张霄潇 , 等 . 中医药临床实践指南:现状和思考 [J]. 中国循证医学杂志 , 2018 , 18 ( 12 ): 1386 - 1390 .
中华人民共和国中央人民政府 . 中国制造2025 [EB/OL]. ( 2016-05-12 )[ 2022-08-16 ]. http://www.gov.cn/zhuanti/2016/MadeinChina2025-plan/mobile.htm http://www.gov.cn/zhuanti/2016/MadeinChina2025-plan/mobile.htm .
国务院办公厅 . 国务院办公厅关于印发“十四五”中医药发展规划的通知 [EB/OL]. ( 2022-03-29 )[ 2022-04-28 ]. http://www.gov.cn/zhengce/content/2022-03/29/content_5682255.htm http://www.gov.cn/zhengce/content/2022-03/29/content_5682255.htm .
AKKUS Z , CAI J , BOONROD A , et al . A Survey of deep-learning applications in ultrasound: artificial intelligence-powered ultrasound for improving clinical workflow [J]. J Am Coll Radiol , 2019 , 16 ( 9B ): 1318 - 1328 .
ZHOU LQ , WANG JY , YU SY , et al . Artificial intelligence in medical imaging of the liver [J]. World J Gastroenterol , 2019 , 25 ( 6 ): 672 - 682 .
MCDONNELL JM , AHERN DP , DOINN T , et al . Surgeon proficiency in robot-assisted spine surgery [J]. Bone Joint J , 2020 , 102 -B( 5 ): 568 - 572 .
OVERLEY SC , CHO SK , MEHTA AI , et al . Navigation and robotics in spinal surgery: where are we now? [J]. Neurosurgery , 2017 , 80 ( 3S ): S86 - S99 .
阮晓钢 . 人工智能专题序言 [J]. 北京工业大学学报 , 2017 , 43 ( 1 ): 3 .
HAMET P , TREMBLAY J . Artificial intelligence in medicine [J]. Metabolism , 2017 , 69 S: S36 - S40 . doi: 10. 1016/j.metabol.2017.01.011 http://dx.doi.org/10.1016/j.metabol.2017.01.011 .
李洪峥 , 高嘉良 , 王阶 . 人工智能:引领中医学新发展的有效工具 [J]. 世界科学技术-中医药现代化 , 2018 , 20 ( 7 ): 1197 - 1201 .
GRANTER SR , BECK AH , PAPKE DJJ . AlphaGo, deep learning, and the future of the human microscopist [J]. Arch Pathol Lab Med , 2017 , 141 ( 5 ): 619 - 621 .
陈勇 , 陈增潭 , 关幼波 , 等 . 关幼波治疗肝炎电子计算机第二诊疗程序临床应用总结 [J]. 辽宁中医杂志 , 1985 ( 2 ): 18 - 19 .
李红岩 , 李灿 , 郎许锋 , 等 . 中医四诊智能化现状及关键技术探讨 [J]. 中医杂志 , 2022 , 63 ( 12 ): 1101 - 1108 .
聂蓉 , 黄杰 . 基于仿生嗅觉的气味指纹检测与识别方法研究 [J]. 河南科学 , 2019 , 37 ( 2 ): 183 - 187 .
孙忠人 , 游小晴 , 韩其琛 , 等 . 人工智能在中医药领域的应用进展及现状思考 [J]. 世界科学技术-中医药现代化 , 2021 , 23 ( 6 ): 1803 - 1811 .
关曼柯 , 魏旭煦 , 赵晨 , 等 . 循证决策模式下中医临床个体化疗效评价研究的定位与未来发展路径 [J]. 中国循证医学杂志 , 2020 , 20 ( 10 ): 1124 - 1129 .
刘续宝 , 孙业桓 . 临床流行病学与循证医学 [M]. 5版 . 北京 : 人民卫生出版社 , 2018 : 1 - 3 .
HOSNY A , PARMAR C , QUACKENBUSH J , et al . Artificial intelligence in radiology [J]. Nat Rev Cancer , 2018 , 18 ( 8 ): 500 - 510 .
李星宇 , 雷禹 , 黄晓旗 , 等 . 基于AI与人工阅片对肋骨骨折性质诊断价值的比较 [J]. 中国医疗设备 , 2022 , 37 ( 8 ): 32 - 36 .
王丽婷 , 刘长松 , 魏玮 , 等 . 中医学术客观化、智能化传承的思考及初步实现 [J]. 中医杂志 , 2021 , 62 ( 12 ): 1036 - 1039 .
赵国桢 , 李博 , 王雅凡 , 等 . 中医药治疗流感临床实践指南:临床调研研究 [J]. 中国循证心血管医学杂志 , 2021 , 13 ( 6 ): 657 - 660 .
张婷婷 , 王亚强 , 温川飙 , 等 . 论智能中医辨证可解释研究的挑战和研究思路 [J]. 中医杂志 , 2022 , 63 ( 6 ): 506 - 510 .
张钰莹 , 周华 , 詹松华 , 等 . 中医四诊新技术的应用及研究进展 [J]. 中国医学计算机成像杂志 , 2021 , 27 ( 1 ): 83 - 86 .
牛婷立 , 杨学智 , 朱庆文 , 等 . 便携式四诊合参辅助诊疗仪的临床试验和临床评价研究 [J]. 北京中医药大学学报 , 2011 , 34 ( 4 ): 231 - 235,289 .
ZHANG H , NI W , LI J , et al . On standardization of basic datasets of electronic medical records in traditional Chinese medicine [J]. Comput Methods Programs Biomed , 2019 , 174 : 65 - 70 . doi: 10.1016/j.cmpb. 2017.12.024 http://dx.doi.org/10.1016/j.cmpb.2017.12.024 .
ZHANG H , NI W , LI J , et al . Artificial intelligence-based traditional Chinese medicine assistive diagnostic system: validation study [J]. JMIR Med Inform , 2020 , 8 ( 6 ): e17608 .
符宇 , 邵明义 , 赵瑞霞 , 等 . 基于中医证据的中医临床疗效评价方法探讨 [J]. 中医杂志 , 2020 , 61 ( 13 ): 1124 - 1129 .
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