Research status and development strategies of intelligent acupuncture clinical decision support system

doi:10.3877/cma.j.issn.2095-3240.2024.02.002

Abstract

Abstract:

The integration of clinical decision support systems (CDSS) is becoming increasingly prevalent in the advancement of smart hospital construction.This technology has the potential to enhance the diagnostic and therapeutic capabilities of healthcare professionals, alleviate the strain on medical resources, and lower healthcare expenditures. Despite these benefits, the application of CDSS within the realm of acupuncture remains in its nascent stage.This paper outlines the concept of CDSS, delves into the historical progression, characteristics and application status of intelligent acupuncture CDSS at different period of time, examines key challenges such as system performance limitations, ethical considerations, and a scarcity of technical expertise, and analyses and summarizes key challenges such as system performance limitations, ethical risk and a scarcity of technical expertise.By providing insights into the future development of intelligent acupuncture CDSS, this research aims to facilitate the intelligent progression of acupuncture.

Key words: Acupuncture and moxibustion therapy, Artificial intelligence, Decision support systems, clinical

Xiaoli Pan, Lili Bai, Shuwen Jin, Jiabao Liu, Manqi Liu, Chuan He, Hongxing Zhang. Research status and development strategies of intelligent acupuncture clinical decision support system[J]. Chinese Journal of Acupuncture and Moxibustion(Electronic Edition), 2024, 13(02): 50-55.

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://zhzjdzzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.2095-3240.2024.02.002

https://zhzjdzzz.cma-cmc.com.cn/EN/Y2024/V13/I02/50

References 31

1	Garg AX，Adhikari NK，McDonald H，et al.Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review[J].JAMA，2005，293(10)：1223-1238.
2	Shortliffe EH，Sepúlveda MJ.Clinical Decision Support in the Era of Artificial Intelligence[J].JAMA，2018，320(21)：2199-2200.
3	刘卓佑，施诚，罗克聪，等．应用电子计算机诊治妇科病[J].贵州医药，1982，7(6)：12-13.
4	刘清，占传杰，刘丰生，等．计算机辅助针灸诊疗专家系统-ZES及其壳体-KZES[J].南昌大学学报(理科版)，1992，16(1)：69-75.
5	姚为民.电脑智能模拟楼百层老中医针灸治病及经穴图象的处理[J].浙江科技简报，1982(5)：14.
6	佘自强.《电子计算机辅助中医针灸诊疗软件》在广东通过技术鉴定[J]. 中国针灸，1987，7(6)：12.
7	江铭炎，陈志坚．具有语音功能的中医针灸专家系统[J].山东大学学报(自然科学版)，1993，43(1)：65.
8	李自双，黄兰，俞为群，等．一种集诊断治疗于一体的针灸专家系统[J].广西科学，1998，5(2)：56-59.
9	宗仁鹤，胡存刚，谭敏，等．基于专家数据库的人体信息诊疗仪的研制[J].激光生物学报，2003，12(1)：63-66.
10	洪文学，裴胜利，李泉，等．基于PC平台专家辅助诊断的针灸系统[A]. 第二十届中国(天津)’2006IT、网络、信息技术、电子、仪器仪表创新学术会议，2006.
11	宋俊杰.基于PC平台的肿瘤辅助治疗系统研究[D].秦皇岛：燕山大学，2006.
12	贺代芳.针灸机械手及其决策支持用针灸诊断专家系统[D].重庆：重庆大学，2001.
13	黄蓓.中医针灸逐步走向人工智能时代[N].中国中医药报，2017-08-23(2).
14	吕训达.基于网络的眼球运动障碍治疗决策支持系统的研究[D].哈尔滨：哈尔滨工程大学，2013.
15	皮勇泽，苏厚勤，黄琴峰．中医针灸临床治疗专家系统的研究与实现[J]. 计算机应用与软件，2015，32(6)：99-103.
16	刘进先，徐天成，张笑兴．世界第一台针灸机器人研制经验总结与启发[J]. 科技与创新，2023 (11)：17-21.
17	张竞心，孙琦，林祺，等．数字经络智能针灸机器人的研发思路探讨[J].中医药导报，2018，24(19)：66-68.
18	刘存志，宓保宏，王丽琼，等．一种用于针灸治疗膝骨关节炎的红外热像辅助选穴系统：CN202210156223.1[P].2022-06-03.
19	谢天宇.针灸治疗膝骨关节炎智能辨证选穴的算法模型研究[D].成都：成都中医药大学，2019.
20	吴冬，孙汉旭，荣培晶，等．针灸与人工智能学科交叉的现状与策略探讨[J]. 针刺研究，2021，46(6)：541-545.
21	王宁.基于电子病历的中医临床决策支持研究[D].合肥：中国科学技术大学，2021.
22	张荣，徐飞．人工智能医学伦理问题及对策研究[J].医学与哲学，2020, 41(13)：14-19.
23	罗芳，陈敏．医疗人工智能的伦理问题及对策研究[J].中国医院管理，2020，40(2)：69-71.
24	谢晋，柳云，边林．人工智能时代背景下移动医疗技术运用的伦理考量[J]. 中国医学伦理学，2020，33(7)：868-872.
25	潘若琳，郑秋莹．人工智能在健康产业应用中的伦理问题分析[J].中国医学伦理学，2019，32(12)：1541-1546.
26	尹涛，何昭璇，孙睿睿，等．机器学习在针灸研究领域的应用现状与展望[J]. 中国针灸，2020，40(12)：1383-1386.
27	郑锐，于广军．临床辅助决策支持系统研究综述[J].中国数字医学，2023, 18(11)：70-77.
28	朱文珍，吕文志．医疗人工智能发展现状及展望[J].放射学实践，2022，37(1)：1-3.
29	赵从朴，袁达，朱溥珏，等．基于CiteSpace的我国临床决策支持研究热点分析[J].中国医院，2023，27(12)：36-38.
30	梅春英，王菡，李晓军，等．智慧医疗的伦理和法律问题及其应对策略[J]. 中国医院管理，2023，43(3)：70-74.
31	朱文兴.智能医工融合新工科人才培养模式探索与实践[J].交通医学，2022，36(5)：463-465.

[1]	Gang Luo, Silin Pan, Lingyu Sun, Zhixin Li, Taotao Chen, Sibo Qiao, Shanchen Pang. Classification of right ventricular hypoplasia in fetuses diagnosed with pulmonary atresia with an intact ventricular septum or critical pulmonary stenosis via a new semantic parsing network model [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2024, 21(04): 377-383.
[2]	Xiaowan Bo, Lehang Guo, Songyuan Yu, Mingzhou Li, Liping Sun. Establishment and verification of an artificial intelligence system for automatic segmentation and classification of thyroid nodules [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2024, 21(03): 304-309.
[3]	Lan He, Zekun Yang, Ying Zhang, Yudong Wang, Weidao Chen, Yitong Wang, E Shen. Diagnostic value of dual-input BCNN-ResNet model for classification of carotid plaque stability on ultrasound images [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2024, 21(02): 137-142.
[4]	Hanlin Cheng, Zhongqing Shi, Zhanru Qi, Xiaoxian Wang, Ziyang Zeng, Chunjie Shan, Sunnan Qian, Shouhua Luo, Jing Yao. Deep learning-based two-dimensional echocardiographic dynamic image view recognition [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2024, 21(02): 128-136.
[5]	Han Liu, Yi Wang, Qinglan Shu, Bo Peng, Lixue Yin, Shenghua Xie. Deep learning-based intelligent assessment of tricuspid valve regurgitation severity by echocardiography [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2024, 21(02): 121-127.
[6]	Peizhi Zhong, Yu Du. Research progress on diagnostic techniques of dental caries [J]. Chinese Journal of Stomatological Research(Electronic Edition), 2024, 18(02): 73-79.
[7]	Boxing Su, Bo Xiao, Jianxing Li. Hot research and interpretation of surgical therapy for stone disease in the annual meeting of American Urology Association in 2024 [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(04): 303-308.
[8]	Linjian Mo, Shubo Yang, Weiyun Nong, Jiwen Cheng. Application of artificial intelligence virtual digital doctors in patient education management for day surgery holmium laser enucleation of the prostate [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(04): 318-322.
[9]	Xingxing Ruan, Zhiyuan Huang, Fuxiang Liu, Jinming Di. Clinical research paper writing based on the perspective of doctors in diagnosing and treating patients [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(04): 397-401.
[10]	Hai Huang, Bisheng Cheng, Jian Huang. 2024 Annual Meeting of European Association of Urology: frontier exploration and future trends in prostate cancer research [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(03): 202-207.
[11]	Liangjie Xie, Jian Wang, Tao Yang. Value analysis of CT image features based on AI in differential diagnosis of benign and malignant Pulmonary nodules [J]. Chinese Journal of Lung Diseases(Electronic Edition), 2024, 17(02): 242-246.
[12]	Ziyang Peng, Zhibo Wang, Dan Wang, Haoqian Peng, Lei Wang, Wei Peng, Juanjuan Wang, Yu Li, Xuemin Liu, Rongqian Wu, Junxi Xiang, Yi Lyu. Application of intelligent auxiliary real-time image defogging technology in laparoscopic cholecystectomy [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2024, 13(03): 328-333.
[13]	Li Dong, Heyan Li, Wenbin Wei. Advances on the application progress of artificial intelligence in diabetic retinopathy [J]. Chinese Journal of Ophthalmologic Medicine(Electronic Edition), 2024, 14(01): 57-61.
[14]	Xianli Zhu, Shousen Wang. Prospects of large language model in medical archive recording of traumatic brain injury [J]. Chinese Journal of Neurotraumatic Surgery(Electronic Edition), 2024, 10(01): 55-57.
[15]	Chenyue Hu, Xianxiu Ge, Xueting Deng, Jianan Yao, Lin Miao. Diagnosis of early gastric cancer and precancerous lesions by magnifying image-enhanced endoscopy [J]. Chinese Journal of Gastrointestinal Endoscopy(Electronic Edition), 2024, 11(01): 47-51.

Please choose a citation manager

Content to export