The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine

Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

Feasibility and Challenges of Interactive AI for Traditional Chinese Medicine: An Example of ChatGPT

As a complementary and alternative medicine(CAM),traditional Chinese medicine(TCM)represents an established medical system with a rich history and abundant clinical experience.TCM is an empirical medicine,the process of which is analogous to ChatGPT’s learning and development model.In TCM,inquiry is a relatively objective way of traditional syndrome differentiation.Although various artificial intelligence systems related to TCM consultation exist,their interactive abilities remain limited.The study standardized the primary complaint and instructed ChatGPT to simulate a TCM practitioner,conducting three comprehensive inquiry tests.The results yielded unexpected conclusions,revealing that ChatGPT could simulate a TCM practitioner’s inquiry with patients,confirming its potential in the field of TCM inquiry.However,current applications still pose certain limitations and risks.Hence,to integrate ChatGPT-like language models with traditional TCM AI to establish an associative mode that can facilitate TCM diagnosis and treatment with more convenience and standardization is crucial,yet at the same time,it should be treated very carefully.

Artificial intelligence meets traditional Chinese medicine: a bridge to opening the magic box of sphygmopalpation for pulse pattern recognition

Artificial intelligence(AI) aims to mimic human cognitive functions and execute intellectual activities like that performed by humans dealing with an uncertain environment. The rapid development of AI technology provides powerful tools to analyze massive amounts of data, facilitating physicians to make better clinical decisions or even replace human judgment in healthcare.Advanced AI technology also creates novel opportunities for exploring the scientific basis of traditional Chinese medicine(TCM) and developing the standardization and digitization of TCM pulse diagnostic methodology. In the present study, we review and discuss the potential application of AI technology in TCM pulse diagnosis. The major contents include the following aspects:(1) a brief introduction of the general concepts and knowledge of TCM pulse diagnosis or palpation,(2) landmark developments in AI technology and the applications of common AI deep learning algorithms in medical practice,(3) the current progress of AI technology in TCM pulse diagnosis,(4) challenges and perspectives of AI technology in TCM pulse diagnosis. In conclusion, the pairing of TCM with modern AI technology will bring novel insights into understanding the scientific principles underlying TCM pulse diagnosis and creating opportunities for the development of AI deep learning technology for the standardization and digitalization of TCM pulse diagnosis.

Application of artificial intelligence in tongue diagnosis of traditional Chinese medicine:A review

Tongue diagnosis is an important process to non-invasively assess the condition of a patient’s internal organs in traditional Chinese medicine(TCM)and each part of the tongue is related to corresponding internal organs.Due to continuing computer technological advances,especially the artificial intelligence(AI)methods have achieved significant success in tackling tongue image acquisition,processing,and classification,novel AI methods are being introduced in traditional Chinese medicine tongue diagnosis medical practices.Traditional tongue diagnose depends on observations of tongue characteristics,such as color,shape,texture,moisture,etc.by traditional Chinese medicine physicians.The appearance of the tongue color,texture and coating reflects the improvement or deterioration of patient’s conditions.Moreover,AI can now distinguish patient’s condition through tongue images,texture or coating,which is all possible increasingly with help from traditional Chinese medicine physicians under the traditional Chinese medicine tongue theory.AI has enabled humans to do what was previously unimagined:traditional Chinese medicine tongue diagnosis with feeding a large amount of tongue image and tongue texture/coating data to train the AI modes.This review focuses on the research advances of AI in TCM tongue diagnosis thus far to identify the major scientific methods and prospects.In this article,we tried to review the AI application in resolving the tongue diagnosis of traditional Chinese medicine on color correction,tongue image extraction,tongue texture/coating segmentation.

Clinical Comparison and Analysis of Decoction of Traditional Chinese Medicine Combined with Ear Acupoint Application and Simple Artificial Tears in the Treatment of Dry Eye Syndrome

OBJECTIVE: To study the clinical comparison and analysis of decoction of Traditional Chinese Medicine(TCM) combined with ear acupoint application and simple artificial tears in the treatment of dry eye syndrome. METHODS:A total of 62 patients(124 eyes) with dry eye syndrome treated in the Department of Ophthalmology of The 4th People's Hospital of Shenyang from July 2017 to March 2018 were selected and equally divided into 2 groups according to the admission order. The observation group received the combination therapy of TCM decoction and ear acupoint application, while the control group was given the simple artificial tears. The symptom score after 2 weeks, 4 weeks, and 8 weeks as well as the indicators including break-up time(BUT), Schirmer I test(SIT) and fluorescein(FL) were recorded and compared between groups. RESULTS: The symptom scores had no difference before treatment(P > 0.05), and were better in the observation group than those in the control group after treatment(P < 0.05). At 2 weeks, 4 weeks, and 8 weeks after the treatment, the amelioration level of BUT, SIT, and FL indicators in the observation group was better than that of the control group(P < 0.05). CONCLUSION: Compared with the artificial tears treatment method, the TCM decoction combined with ear acupoint application can significantly ameliorate the tear film stability, tear secretion, and reduce ocular surface damage for dry eye patients.

A brief overview of traditional Chinese medicine prescription powered by artificial intelligence

Traditional Chinese medicine prescription is one of the treasures of traditional Chinese medicine(TCM).There are tens of thousands TCM prescriptions accumulated in the past thousands of years,corresponding to different diseases,symptoms and therapeutic goals.The correspondences are so complicated that there is an urgent need to leverage new technologies such as artificial intelligence(AI)to analyze,understand and utilize them effectively.In this paper,we present a brief overview of this direction,where current research progress on TCM prescription powered by AI is summarized.Our summarization focuses on three aspects,TCM prescription mining that aims at understanding the TCM prescription,TCM prescription or herb knowledge base construction that aims at extracting knowledge to support the TCM prescription-related study,and TCM prescription discovery that aims at utilizing AI technologies to further energize TCM.It is encouraging to see that steady progress in this direction has been made recently.Besides,a toy experiment on image-based TCM herb recognition by using convolutional neural networks is also conducted.It basically verifies that it is promising to use AI technologies to address challenging tasks in TCM.We also point out several research topics that could be cooperatively performed by researchers from the two disciplines.

Artificial intelligence for the development and implementation guidelines for traditional Chinese medicine and integrated traditional Chinese and western medicine

The translation and implementation of clinical practice guidelines(CPGs)for Traditional Chinese Medicine(TCM)and Integrated Traditional Chinese and Western medicine is crucial to the adoption of medical science and technology,but the low operability and slow update of integrated traditional Chinese and Western Medicine guidelines,and the lack of integration between guidelines and clinical practice,result in the guidelines not having the desired clinical effects in practice.The application of Artificial Intelligence(AI)to the field of CPGs development aims to shorten the development time,optimize and accelerate the whole process of CPG’s development.This article summarized the current research and application status of AI in development and implementation CPGs for TCM and Integrated Traditional Chinese and Western medicine and proposed the method of Combining real world data and AI technology to enrich for TCM and Integrated Traditional Chinese and Western medicine.

Artificial intelligence and its application for cardiovascular diseases in Chinese medicine

Cardiovascular diseases(CVDs)are major disease burdens with high mortality worldwide.Early prediction of cardiovascular events can reduce the incidence of acute myocardial infarction and decrease the mortality rates of patients with CVDs.The pathological mechanisms and multiple factors involved in CVDs are complex;thus,traditional data analysis is insufficient and inefficient to manage multidimensional data for the risk prediction of CVDs and heart attacks,medical image interpretations,therapeutic decision-making,and disease prognosis prediction.Meanwhile,traditional Chinese medicine(TCM)has been widely used for treating CVDs.TCM offers unique theoretical and practical applications in the diagnosis and treatment of CVDs.Big data have been generated to investigate the scientific basis of TCM diagnostic methods.TCM formulae contain multiple herbal items.Elucidating the complicated interactions between the active compounds and network modulations requires advanced data-analysis capability.Recent progress in artificial intelligence(AI)technology has allowed these challenges to be resolved,which significantly facilitates the development of integrative diagnostic and therapeutic strategies for CVDs and the understanding of the therapeutic principles of TCM formulae.Herein,we briefly introduce the basic concept and current progress of AI and machine learning(ML)technology,and summarize the applications of advanced AI and ML for the diagnosis and treatment of CVDs.Furthermore,we review the progress of AI and ML technology for investigating the scientific basis of TCM diagnosis and treatment for CVDs.We expect the application of AI and ML technology to promote synergy between western medicine and TCM,which can then boost the development of integrative medicine for the diagnosis and treatment of CVDs.

Antacid effects of Chinese herbal prescriptions assessed by a modified artificial stomach model

AIM:To assess the antacid effects of the tonic Chinese herbal prescriptions,Si-Jun-Zi-Tang(SJZT) and Shen-Ling-Bai-Zhu-San(SLBZS).METHODS:Decoctions of the tonic Chinese herbal prescriptions,SJZT and SLBZS,were prepared according to Chinese original documents.The pH of the prescription decoctions and their neutralizing effects on artif icial gastric acids were determined and compared with water and the active controls,sodium bicarbonate and colloidal aluminum phosphate.A modified model of Vatier's artificial stomach was used to determine the duration of consistent neutralization effect on artificial gastric acids.The neutralization capacity in vitro was determined with the titration method of Fordtran's model.RESULTS:The results showed that both SJZT and SLBZS have antacid effects in vitro.Compared with the water group,SJZT and SLBZS were found to possess signif icant gastric acid neutralizing effects.The duration for consistent neutralization of SLBZS was signif icantly longer than that of water.Also,SLBZS and SJZT exhibited signif icant antacid capacities compared to water.CONCLUSION:SJZT and SLBZS were consistently active in the artificial stomach model and are suggested to have antacid effects similar to the active control drugs.

中药智慧药学服务的实践与技术分析

目的 分析中药智慧药房的发展现状,总结中药智慧药学服务实践经验,概述其技术要求和发展方向。方法 成都中医药大学附属医院自2018年1月启动智慧中药房项目,建立中药智慧药房,承担门诊中药饮片调剂、煎药、配送等药学服务业务。结果 截至2023年5月已完成中药饮片代煎配送557.2万副,2022年度共服务患者23.14万人次。服务环节更简单,无需等候取药,无需二次到院取药,服务效率高,改善了患者就医体验。结论 中药智慧药学服务发展迅速,未来将依托技术进步建立全程化智慧服务体系。

中医智能诊疗机器人的临床应用研究

研究立足于各类人工智能算法在中医诊断中的应用现状及问题。主要介绍传统机器学习算法以及近年来新兴的深度学习算法与中医四诊相契合的场景;探索将人工智能技术引入中医诊断过程,以进一步推动中医的客观化、定量化发展的智能诊疗机器人设计。针对中国目前中医诊疗仪器在临床领域研发应用现状,引入机器人技术,以促进中医诊疗仪器创新发展,推动中医理论研究与诊疗技术的协同发展,使中医诊疗技术在提高人民健康和生活水平方面发挥重要作用。

“中医治未病+人工智能”助力社区居家养老的对策研究

探寻中医“治未病”与信息化人工智能结合,提升社区居家养老慢病健康管理水平的方法路径。以文献查阅、信息检索和以辽宁省沈阳市8个社区居家养老中心为随机对象的实地调研为主,提出三条决策建议:借力“互联网+”人工智能技术,推进社区居家养老慢病健康管理水平;引入中医药“治未病”思想,建立区域人口中医“治未病”信息化人工智能健康管理监测共享平台;加强基层社区居家养老机构中医“治未病”适宜技术人才的培养和中医药服务供给。

Systems Theory-Driven Framework for AI Integration into the Holistic Material Basis Research of Traditional Chinese Medicine

This paper introduces a systems theory-driven framework to integration artificial intelligence(AI)into traditional Chinese medicine(TCM)research,enhancing the understanding of TCM’s holistic material basis while adhering to evidence-based principles.Utilizing the System Function Decoding Model(SFDM),the research progresses through define,quantify,infer,and validate phases to systematically explore TCM’s material basis.It employs a dual analytical approach that combines top-down,systems theory-guided perspectives with bottom-up,elements-structure-function methodologies,provides comprehensive insights into TCM’s holistic material basis.Moreover,the research examines AI’s role in quantitative assessment and predictive analysis of TCM’s material components,proposing two specific AIdriven technical applications.This interdisciplinary effort underscores AI’s potential to enhance our understanding of TCM’s holistic material basis and establishes a foundation for future research at the intersection of traditional wisdom and modern technology.

基于PDCA循环持续改进的SPOC模式在中医学教学管理中的应用

新型冠状病毒肺炎(以下简称“新冠”)流行3年,对世界各行各业都产生了巨大影响。目前我国新冠疫情防控已取得重大战略成果,疫情总体得到有效控制,社会已经全面复工复学,疫情防控已经转变为常态化管理,但丝毫不能忽视反弹风险,仍然有部分地区出现本土感染病例。这也给疫情常态化防控下,高等医学院校中医学专业教学管理带来新的思考。高等医学院校教职员工、学生众多,为做到在严格疫情防控下减少聚集性中医相关课程教学,避免出现聚集性传播可能,在线教学成为目前主要的教学模式。文章探索了PDCA循环管理系统和小规模限制性在线课程(SPOC)模式在高等医学院校中医学专业教学管理中的应用,以期找到高效、适宜的中医学专业教学管理模式,提高中医学教学质量。

人工智能工具促进分子生物学与中药专业有效融合的探索

分子生物学已成为中医药研究的重要方法,它与中药研究的有机结合是推动中药事业创新发展的关键。如何帮助学生更好地掌握分子生物学知识和技能,并与中药学科进行更有效的融合,文章提出可借助人工智能工具,辅助中药专业学生深入学习分子生物学知识。

人工智能应用于中医药临床研究的现状

目的梳理人工智能在中医药临床研究中的应用现状,为充分发挥人工智能在中医药研究领域的作用提供参考依据。方法检索中国知网、万方、中国科技期刊数据库、PubMed和Web of Science核心数据库,收集公开发表的针对人工智能在中医药临床研究中应用的文献,进行分析。结果最终纳入32篇文献,均来自中国,发文年限在2014—2023年。研究主要来自高校和医疗机构。纳入的文献均为观察性研究,共包含病例47564例。人工智能在中医药临床研究中的应用包含10个方面,排名前三的分别为:(1)根据中医证型预测疾病发生风险,预测准确率均在80%以上;(2)预测疾病的中医证型,预测准确率高达99.16%;(3)利用人工智能探索疾病的中医证型与理化指标的关联,准确率最高达96.4%。其余7个分别为利用人工智能挖掘并构建了舌图像与疾病的关联模型、辅助诊断、根据中医人格及体质预测疾病发生风险、预测疾病预后、根据中医脉象信号预测疾病发生风险、预测中成药不良反应发生率。结论人工智能在中医药临床研究中赋能效果明显,可有效提高患者的诊疗质量,避免医疗资源的浪费。

加用中药周期疗法改善IUI患者妊娠结局的临床研究

[目的]观察加用中药周期疗法改善宫腔内人工授精(IUI)患者妊娠结局的临床效果。[方法]将40例行诱导排卵联合IUI的脾肾两虚型排卵障碍性不孕患者,分为中药周期疗法联合诱导排卵组(治疗组)20例,单纯诱导排卵组(对照组)20例,比较两组临床疗效、扳机日子宫内膜厚度和形态、排卵率及妊娠率。[结果]治疗组总有效率为95%,对照组为60%,两组差异有统计学意义(P<0.05)。治疗组扳机日子宫内膜厚度、A型内膜比例较对照组显著增加(P<0.05)。治疗组和对照组患者的排卵率相当(P>0.05)。治疗组妊娠率为45%,对照组为15%,两组差异有统计学意义(P<0.05)。[结论]在宫腔内人工授精周期中,使用中药周期疗法能使子宫内膜增厚,改善子宫内膜容受性,从而提高妊娠率。

动态不确定因果图在中医诊断中的应用探讨

动态不确定因果图(DUCG)已成为中医药领域新兴的、先进的知识表示与推理模型。为更好地应用DUCG为中医临床提供诊断推理与决策支持,在归纳总结DUCG中医药领域研究与应用情况的基础上,分析现阶段DUCG在中医诊断中存在的主要问题,包括中医术语规范统一和中医药知识库质量问题、推理算法和模型建造的方法选择与设计问题、DUCG中医诊断模型的平台化和产品化问题等,并据此展开应用思路与方法探讨,提出应深挖DUCG的技术内涵,根据临床实际需求选择精准、高效的推理建模方法,建立符合中医药理论思想、具有中医特色的智能辅助诊断模型,加强DUCG协同研究平台及产品的开发应用。

从循证中医到智慧中医:自动系统评价技术和中医快速循证决策

循证中医从产生到发展极大推动了中医决策科学化和规范化,但传统证据产生模式无法满足快速循证决策需求。基于自动系统评价技术的中医药快速决策模式是智慧中医的典型案例,这种“端到端”循证决策模式在“中医药临床证据自动分析及可视化平台”得到验证。

数字技术在中医药科技创新中的应用及未来发展趋势

数字化是中医药发展的必然选择,是新形势下中医药科技创新的新动能。随着我国数字经济的不断发展,数字化对中医药科技创新更加重要。系统梳理了当前中医药领域数字化转型发展的现状,从数字技术在中医药科技创新中的应用现状、未来发展趋势、面临的挑战与对策建议三大方面论述了数字技术在中医药科技创新中的地位与作用。在当下和今后很长一段时间,数字化将持续大力推动中医药科技创新,促进中医药科学技术快速发展。