New evidence-based practice:Artificial intelligence as a barrier breaker

The concept of evidence-based practice has persisted over several years and remains a cornerstone in clinical practice,representing the gold standard for optimal patient care.However,despite widespread recognition of its significance,practical application faces various challenges and barriers,including a lack of skills in interpreting studies,limited resources,time constraints,linguistic competencies,and more.Recently,we have witnessed the emergence of a groundbreaking technological revolution known as artificial intelligence.Although artificial intelligence has become increasingly integrated into our daily lives,some reluctance persists among certain segments of the public.This article explores the potential of artificial intelligence as a solution to some of the main barriers encountered in the application of evidence-based practice.It highlights how artificial intelligence can assist in staying updated with the latest evidence,enhancing clinical decision-making,addressing patient misinformation,and mitigating time constraints in clinical practice.The integration of artificial intelligence into evidence-based practice has the potential to revolutionize healthcare,leading to more precise diagnoses,personalized treatment plans,and improved doctor-patient interactions.This proposed synergy between evidencebased practice and artificial intelligence may necessitate adjustments to its core concept,heralding a new era in healthcare.

Exploration and Practice on Artificial Intelligence Information Technology Intergration into Practical Teaching of Acupuncture and Massage in the Background of New Medicine

[Objectives]In order to fully leverage the distinctive features of the top-tier national professional discipline of acupuncture and massage.[Methods]According to the characteristics of the scientific attributes of acupuncture and massage,combined with the top-tier na-tional professional AI practical teaching platform and artificial intelligence-related information technology,together with the teaching team with rich teaching experience.[Results]Innovative reforms and practical explorations are being conducted to integrate AI information technology into acupuncture and massage practical teaching under the background of new medicine.[Conclusions]Through practical research,the quali-ty of the practical teaching of students in acupuncture and massage major has been improved,playing a leading and exemplary role in related majors across the country.

Machine learning applications in healthcare clinical practice and research

Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.

Exploration and Application of Ubiquitous Mapping in Engineering Practice Courses in the Intelligence Age

In the current era of digital surveying and mapping to intelligent surveying and mapping,ubiquitous surveying and mapping has brought many opportunities and challenges to college engineering course teaching.With the development of ubiquitous surveying and mapping,college engineering practice courses urgently need to respond to ubiquitous surveying and mapping.The research aims to integrate the development of ubiquitous surveying and mapping into the teaching of engineering practice courses in colleges,including promoting Android,Brower/Server(B/S),and Client/Server(C/S)to build a platform for practice courses.This also incorporates real development cases in measurement data processing such as gravity field refinement.In this way,the teaching level of engineering practice courses in colleges can be improved,and new ideas can be put forward for cultivating surveying and mapping talents in the new era in colleges.Finally,it can also provide new ideas for the organization of surveying and mapping practice courses under the background of the pandemic.

Strategic information perception methods and practices in the open source intelligence

Open source intelligence is one of the most important public data sources for strategic information analysis. One of the primary and core issues of strategic information research is information perception,so this paper mainly expounds the perception method for strategic information perception in the open source intelligence environment as well as the framework and basic process of information perception. This paper argues that in order to match the information perception result with the information depiction result,it conducts practical exploration for the results of information acquisition,perception,depiction and analysis. This paper introduces and develops a monitoring platform for information perception. The results show that the method proposed in this paper is feasible.

Artificial Intelligence;a Pragmatic Approach to Implementation in Medicine, a Review of the literature and a Survey of Local Practice in Midlands in UK

The use of Artificial Intelligence (AI) for clinical pathway management and decision making is believed to improve clinical care and has been used to improve pathways for treatment in most medical disciplines. Methods: A literature review was undertaken to identify the hurdles and steps required to introduce supported clinical decision-making using AI within hospitals. This was supported by a survey of local hospital practice within the Midlands of the United Kingdom to see what systems had been introduced and were functioning effectively. Results: It is unclear how to practically implement systems using AI within medicine easily. Algorithmic medicine based on a set of rules calculated from data only takes a clinician so far to deliver patient centred optimal treatment. AI facilitates a clinician’s ability to assimilate data from disparate sources and can help with some of the analysis and decision making. However, learning remains organic and the subtleties of difference between patients, care providers who exhibit non-verbal communication for instance make it difficult for an AI to capture all the pertinent information required to make the correct clinical decision for any given individual. Hence it assists rather than controls any process in clinical practice. It also must continually renew and adapt considering changes in practise and trends as the goalposts change to meet fluctuations in resources and workload. Precision surgery is benefiting from robotic-assisted surgery in parts driven by AI and being used in 80% of trusts locally. Conclusion: The use of AI in clinical practice remains patchy with it being adopted where research groups have studied a more effective method of monitoring or treatment. The use of robotic-assisted surgery on the other hand has been more rapid as the precision of treatment that this provides appears attractive in improving clinical care.

Teaching for Learning Styles and Multiple Intelligences: a Personal Reflection

The paper reviewed what the literature has said about learning styles and multiple intelligences. By practicing a personal reflection on learning styles and multiple intelligences, the paper indicated that teachers need make paradigm shift respecting the fact that every student is gifted and can be taught with the same contents, approaches and assessment. Teaching for diversity should be implemented.

Intelligent Reflecting Surfaces Enabled Cognitive Internet of Things Based on Practical Pathloss Model

In this paper,we aim to unlock the potential of intelligent reflecting surfaces(IRSs)in cognitive internet of things(loT).Considering that the secondary IoT devices send messages to the secondary access point(SAP)by sharing the spectrum with the primary network,the interference is introduced by the IoT devices to the primary access point(PAP)which profits from the IoT devices by pricing the interference power charged by them.A practical path loss model is adopted such that the IRSs deployed between the IoT devices and SAP serve as diffuse scatterers,but each reflected signal can be aligned with its own desired direction.Moreover,two transmission policies of the secondary network are investigated without/with a successive interference cancellation(SIC)technique.The signal-to-interference plus noise ratio(SINR)balancing is considered to overcome the nearfar effect of the IoT devices so as to allocate the resource fairly among them.We propose a Stackelberg game strategy to characterize the interaction between primary and secondary networks.For the proposed game,the Stackelberg equilibrium is analytically derived to optimally obtain the closed-form solution of the power allocation and interference pricing.Numerical results are demonstrated to validate the performance of the theoretical derivations.

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.

Research on the Application of Big Data and Artificial Intelligence Technology in Computer Network

With the continuous development of social economy,science and technology are also in continuous progress,relying on the Internet technology of big data era has come in an all-round way.On the basis of the development of cloud computing and Internet technology,artificial intelligence technology has emerged as the times require.It also has more advantages.Applying it to computer network technology can effectively improve the data processing efficiency and quality of computer network technology,and improve the convenience for people’s life and production.This paper studies and analyzes the practical application requirements of computer network,and discusses the application characteristics and timeliness of artificial intelligence technology.

A Discussion on the Practical Teaching Reform of Intelligent Mobile Terminal Technology Course

In this intelligent era,there is a high market demand for professional engineering talents in the computer industry.Based on engineering education accreditation,this paper briefly discusses the practical teaching reform of the intelligent mobile terminal technology course,which involves integrating theory with practical,taking students as the center,focusing on practical teaching,strengthening students’practical skills and computer application development skills,as well as promoting the construction and development of engineering accreditation.

Artificial intelligence-based predictive model of nanoscale friction using experimental data

A recent systematic experimental characterisation of technological thin films,based on elaborated design of experiments as well as probe calibration and correction procedures,allowed for the first time the determination of nanoscale friction under the concurrent influence of several process parameters,comprising normal forces,sliding velocities,and temperature,thus providing an indication of the intricate correlations induced by their interactions and mutual effects.This created the preconditions to undertake in this work an effort to model friction in the nanometric domain with the goal of overcoming the limitations of currently available models in ascertaining the effects of the physicochemical processes and phenomena involved in nanoscale contacts.Due to the stochastic nature of nanoscale friction and the relatively sparse available experimental data,meta-modelling tools fail,however,at predicting the factual behaviour.Based on the acquired experimental data,data mining,incorporating various state-of-the-art machine learning(ML)numerical regression algorithms,is therefore used.The results of the numerical analyses are assessed on an unseen test dataset via a comparative statistical validation.It is therefore shown that the black box ML methods provide effective predictions of the studied correlations with rather good accuracy levels,but the intrinsic nature of such algorithms prevents their usage in most practical applications.Genetic programming-based artificial intelligence(AI)methods are consequently finally used.Despite the marked complexity of the analysed phenomena and the inherent dispersion of the measurements,the developed AI-based symbolic regression models allow attaining an excellent predictive performance with the respective prediction accuracy,depending on the sample type,between 72%and 91%,allowing also to attain an extremely simple functional description of the multidimensional dependence of nanoscale friction on the studied variable process parameters.An effective tool for nanoscale friction prediction,adaptive control purposes,and further scientific and technological nanotribological analyses is thus obtained.

Current state and predicted technological trends in global railway intelligent digital transformation

Purpose–In recent years,railway systems worldwide have faced challenges such as the modernization of engineering projects,efficient management of intelligent digital railway equipment,rapid growth in passenger and freight transport demands,customized transport services and ubiquitous transport safety.The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry,thereby becoming an inevitable global trend in railway development.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the current state of global railway intelligent digital transformation,focusing on the characteristics and applications of intelligent digital transformation technology.It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation,theoretically elucidating the development process of global railway intelligent digital transformation and,in practice,providing guidance and empirical examples for railway intelligence and digital transformation.Findings–Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution,progressing from the early stages,to a period of increasing attention and popularity,then to a phase of declining interest,followed by a resurgence and ultimately reaching a mature stage.Originality/value–The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution,accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

面向智能制造仿真实验的产线数字孪生建模

针对智能制造领域人才培养中,实践教学存在的成本高、安全保证难等问题,该研究构建了智能制造仿真实验系统。首先,以智能产线为基础、车间信息化平台为桥梁,融合产线数字孪生技术,构建了面向智能制造仿真实验的数字孪生系统框架;其次,对系统中包含的产线物理实体模型、数据采集及车间信息化平台、数字孪生产线的多维度模型及智能制造仿真实验平台展开了详细阐述;最后设计产线生产调度优化实验,验证了该数字孪生仿真实验系统的有效性。

人工智能背景下高校思政教育创新的实践困境与解决对策

人工智能的迅速发展进一步推动了高校教育的变革,数字化智能技术正在逐渐重塑教育的新形态,而人工智能与教育的融合发展,成了智能时代的一大趋势。在此契机下,高校思想政治教育工作者需要抓住机遇,改变传统的思政教育模式,开创出符合时代发展潮流的高校思想政治教育新模式,并为新时代高校思政教育赋能。在这一数字化生态系统中,将人工智能技术应用于教学平台、智能评估和辅导系统等方面,以提供更加精准和个性化的服务,增强学生的学习体验;将人工智能技术与思政教育相结合,创新工作方式和方法;建立高校思政教育工作机制,以确保整个教育过程的科学管理和有效运营。

基于赛教融合的智能交通课程实践教学研究

结合全国大学生智能汽车竞赛百度智慧交通创意组竞赛项目,设计智能交通课程实践教学内容,从竞赛内容凝练与课程知识点结合的教学案例和实验项目,实现赛教资源融合和赛教一体化实践平台共享。设计的实验教学项目融合了图像处理、数据分析、人工智能、智能车硬件平台等内容,包括数据采集、数据分析、数据集构建,深度学习模型建立与智能车平台部署等实践环节。学生从编写简单程序开始,不断提高,到构建复杂的深度学习模型实现智能车自动巡航控制实验。将竞赛任务具有挑战性和对抗性的特点融入课程教学,吸引学生兴趣,增强学生求知欲,提升学生创新能力和工程实践能力。

化工安全技术课程智慧教学改革的探索与实践

化工安全技术课程是面向高职化工类专业学生的一门重要专业核心课程。为满足高素质技术技能型人才培养需求,聚焦课程教学中的问题,坚持以服务学生全面发展为中心的理念,从课程内容重构、教学资源建设、考核与评价体系构建、智慧教学实施流程等方面,进行了智慧教学改革的探索,以期为化工类专业智慧教学改革提供参考。

基于数字孪生的模块化生产系统实践教学平台设计与实现

该文将数字孪生技术应用于模块化生产系统(modular production system,MPS)的智能化改造中,构建了基于数字孪生的MPS实践教学平台。依托监控系统和虚实交互等关键技术,增加了MPS数字孪生体的虚拟建模、虚实联调和PLC程序软件在环/硬件在环调试等实训环节;验证了MPS实践教学平台设计方案的可行性;制定了新的教学框架及详细的实训内容和考核方案。最后,将实训内容与大学生竞赛相结合,提高了学生对智能制造、工业生产的认知能力和实践动手能力。

人工智能新时代下教学改革的新思考

随着ChatGPT-4的推出,人工智能技术的发展与应用进入了一个崭新的时代,也必然对现代科技人才的培养产生深远的影响。本文首先简述了人工智能技术及其在化学研究中的应用;其次,探讨了在人工智能新时代下化学专业学生创新能力培养的新要求;最后,介绍了我院《化学信息学》课程教学改革的探索与实践。

医院智慧消防实践探索

医院消防安全管理不仅是医院安全管理中的重点,更肩负着保障医院内部医患生命财产安全的重要使命,随着智能化技术的不断发展,消防安全行业也逐步向着智能化、数字化、网络化的方向发展。文章结合广东省第二人民医院智慧消防实践情况,积极探索新形势下智慧消防建设应用新模式,以期为各大医院筑牢消防安全屏障提供借鉴。