Artificial intelligence technology and ultrasound-guided nerve block for analgesia in total knee arthroplasty

BACKGROUND Knee diseases are more common in middle-aged and elderly people,so artificial knee replacement is also more used in middle-aged and elderly people.Although the patient’s pain can be reduced through surgery,often accompanied by moderate pain after surgery and neutralization,which not only increases the psychological burden of the patient,but also greatly reduces the postoperative recovery effect,and may also lead to the occurrence of postoperative adverse events in severe cases.AIM To investigate the analgesic effect of artificial intelligence(AI)and ultrasoundguided nerve block in total knee arthroplasty(TKA).METHODS A total of 92 patients with TKA admitted to our hospital from January 2021 to January 2022 were opted and divided into two groups according to the treatment regimen.The control group received combined spinal-epidural anesthesia.The research group received AI technique combined with ultrasound-guided nerve block anesthesia.The sensory block time,motor block time,visual analogue scale(VAS)at different time points and complications were contrasted between the two groups.RESULTS The time of sensory block onset and sensory block perfection in the research group was shorter than those in the control group,but the results had no significant difference(P>0.05).Duration of sensory block in the research group was significantly longer than those in the control group(P<0.05).The time of motor block onset and motor block perfection in the research group was shorter than those in the control group,but the results had no significant difference(P>0.05).Duration of motor block in the research group was significantly longer than those in the control group.The VAS scales of the research group were significantly lower than that of the control group at different time points(P<0.05).The postoperative hip flexion and abduction range of motion in the research group were significantly better than those in the control group at different time points(P<0.05).The incidence of complications was significantly lower in the research group than in the control group(P=0.049).CONCLUSION In TKA,the combination of AI technology and ultrasound-guided nerve block has a significantly effect,with fewer postoperative complications and significantly analgesic effect,which is worthy of application.

Use of artificial intelligence in total mesorectal excision in rectal cancer surgery: State of the art and perspectives

BACKGROUND Colorectal cancer is a major public health problem,with 1.9 million new cases and 953000 deaths worldwide in 2020.Total mesorectal excision(TME)is the standard of care for the treatment of rectal cancer and is crucial to prevent local recurrence,but it is a technically challenging surgery.The use of artificial intelligence(AI)could help improve the performance and safety of TME surgery.AIM To review the literature on the use of AI and machine learning in rectal surgery and potential future developments.METHODS Online scientific databases were searched for articles on the use of AI in rectal cancer surgery between 2020 and 2023.RESULTS The literature search yielded 876 results,and only 13 studies were selected for review.The use of AI in rectal cancer surgery and specifically in TME is a rapidly evolving field.There are a number of different AI algorithms that have been developed for use in TME,including algorithms for instrument detection,anatomical structure identification,and image-guided navigation systems.CONCLUSION AI has the potential to revolutionize TME surgery by providing real-time surgical guidance,preventing complic-ations,and improving training.However,further research is needed to fully understand the benefits and risks of AI in TME surgery.

Framework and Key Technologies of Human-machine Hybrid-augmented Intelligence System for Large-scale Power Grid Dispatching and Control

With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way.

Heading toward Artificial Intelligence 2.0

With the popularization of the Intemet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence （AI） has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage： AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the develoDment of Al 2.0 are given.

Human-Machine Shared Lateral Control Strategy for Intelligent Vehicles Based on Human Driver Risk Perception Reliability

Intelligent vehicle(Ⅳ)technology has developed rapidly in recent years.However,achieving fully unmanned driving still presents numerous challenges,which means that human drivers will continue to play a vital role in vehicle operation for the foreseeable future.Human-machine shared driving,involving cooperation between a human driver and an automated driving system(AVS),has been widely regarded as a necessary stage for the development of IVs.Focusing onⅣdriving safety,this study proposed a human-machine shared lateral control strategy(HSLCS)based on the reliability of driver risk perception.The HSLCS starts by identifying the effective areas of driver risk perception based on eye movements.It establishes an anisotropic driving risk field,which serves as the foundation for the AVS to assess risk levels.Building upon the cumulative and diminishing effects of risk perception,the proposed approach leverages the driver's risk perception effective area and converts the risk field into a representation aligned with the driver's perspective.Subsequently,it quantifies the reliability of the driver's risk perception by using area-matching rules.Finally,based on the driver’s risk perception reliability and dif-ferences in lateral driving operation between the human driver and the AVS,the dynamic distribution of driving authority is achieved through a fuzzy rule-based system,and the human-machine shared lateral control is completed by using model predictive control.The HSLCS was tested across various scenarios on a driver-in-the-loop test platform.The results show that the HSLCS can realize the synergy and complementarity of human and machine intelligence,effectively ensuring the safety ofⅣoperation.

Swarm Intelligence Research:From Bio-inspired Single-population Swarm Intelligence to Human-machine Hybrid Swarm Intelligence

Swarm intelligence has become a hot research field of artificial intelligence.Considering the importance of swarm intelli-gence for the future development of artificial intelligence,we discuss and analyze swarm intelligence from a broader and deeper perspect-ive.In a broader sense,we are talking about not only bio-inspired swarm intelligence,but also human-machine hybrid swarm intelli-gence.In a deeper sense,we discuss the research using a three-layer hierarchy:in the first layer,we divide the research of swarm intelli-gence into bio-inspired swarm intelligence and human-machine hybrid swarm intelligence;in the second layer,the bio-inspired swarm intelligence is divided into single-population swarm intelligence and multi-population swarm intelligence;and in the third layer,we re-view single-population,multi-population and human-machine hybrid models from different perspectives.Single-population swarm intel-ligence is inspired by biological intelligence.To further solve complex optimization problems,researchers have made preliminary explor-ations in multi-population swarm intelligence.However,it is difficult for bio-inspired swarm intelligence to realize dynamic cognitive in-telligent behavior that meets the needs of human cognition.Researchers have introduced human intelligence into computing systems and proposed human-machine hybrid swarm intelligence.In addition to single-population swarm intelligence,we thoroughly review multi-population and human-machine hybrid swarm intelligence in this paper.We also discuss the applications of swarm intelligence in optimization,big data analysis,unmanned systems and other fields.Finally,we discuss future research directions and key issues to be studied in swarm intelligence.

Interaction and the Genesis of Experience: A Phenomenological Contribution for Meaningful Embodied Artificial Intelligence

In this article I will address the issue of the meaning of Embodied Artificial Intelligence(EAI)as it is configured today.My starting point is the refined interactive perspective on the semantics of EAI,as was recently suggested by Froese and colleagues.This perspective rests on the assumption that the concept of human bodily subjectivity must be extended to include meaning-making processes,which are enabled by advanced AI systems that may be incorporated in the human biological body.After having clarified the technical background,I will introduce the genetic component of the phenomenological method as a suitable tool to face the aforementioned issue.Towards this end,I will place the genetic method in the context of the so-called New Human-Machine Interaction(New HMI).I will further outline a genetic phenomenology of visual embodiment,suggesting a futuristic application based on the thesis of the“technological supplementation of phenomenological methodology”through the synthetic method.The case at stake is that of patients with a severe clinical picture characterised by the loss of corneal function,who in the near future could be treated with synthetic corneal prosthetic implants produced by a 3D bio-printing process by using an advanced EAI technique.I will conclude this article with a brief review of the main problems that still remain open.

人工智能影响我国全要素生产率的机制与效应研究

人工智能作为引领新一轮科技革命与产业变革的战略性技术,具有溢出带动性很强的“头雁”效应,有利于提升全要素生产率。本文分别基于宏观省级层面和微观企业层面的数据,利用企业机器人数据和智能制造试点示范项目的准自然实验,采用交叠DID和双重机器学习等方法实证识别了人工智能对全要素生产率的作用效应。研究结果表明,人工智能发展应用在宏观和微观两个维度均较为显著地促进了我国全要素生产率的提升。在宏观层面,人工智能对东部沿海地区全要素生产率的作用效应强于对中西部地区的影响;对高市场竞争环境下的全要素生产率作用效应更明显。在微观层面,人工智能对低技术企业全要素生产率的影响强于对高技术企业的影响,对规模较大企业的影响强于对规模较小企业的影响。人工智能提升全要素生产率的机制包括提高要素配置效率、降低企业成本和增强企业研发能力。本文研究结论对于进一步深化人工智能与实体经济融合,提升全要素生产率,实现经济高质量发展具有明确意义。

基于人工智能动态影像识别的全膝关节置换术后早期步态分析研究

目的:探讨全膝关节置换术(total knee arthroplasty,TKA)术后的早期步态特征及临床结果。方法:自2023年2月到2023年7月采用TKA治疗单侧膝骨关节炎(knee osteoarthritis,KOA)患者26例,男4例,女22例;年龄57~85(67.58±6.49)岁;身体质量指数(body mass index,BMI)为18.83~38.28(26.43±4.15)kg·m^(-2);左膝14例,右膝12例;Kellgren-Lawrence分级,Ⅲ级6例,Ⅳ级20例;病程1~14(5.54±3.29)年。使用智能手机分别于术前、术后6周拍摄患者起立行走、行走侧拍、蹲起、仰卧屈膝的影像视频,通过人体姿势估计框架OpenPose分析步频、步长、步长时间、步速、膝关节主动屈膝角度、步幅、双下肢支撑相时间以及蹲姿中最大屈髋、屈膝角度。分别于术前及术后6周采用Western Ontario and McMaster大学骨关节炎指数(Western Ontario and McMaster Universities Osteiarthritis Index,WOMAC)评分和美国膝关节协会(Knee Society score,KSS)进行临床疗效评价。结果:所有患者获得随访,时间5~7(6.00±0.57)周。WOMAC总分由术前的(64.85±11.54)分,减少至术后6周的(45.81±7.91)分(P<0.001);KSS由术前(101.19±9.58)分,提高至术后6周的(125.50±10.32)分(P<0.001)。患侧步速、步频、步幅分别由术前的(0.32±0.10)m·s^(-1)、(96.35±24.18)步·分^(-1)、(0.72±0.14)m,提高至术后的6周的(0.48±0.11)m·s^(-1)、(104.20±22.53)步·分^(-1)、(0.79±0.10)m(P<0.05)。双下肢支撑时间和主动屈膝角度由术前的(0.31±0.38)s、(125.21±11.64)°,减少至术后6周的(0.11±0.04)s、(120.01±13.35)°(P<0.05)。术前可以完成蹲起动作的11例,术后6周可以完成的13例,术前和术后6周同时可以完成的9例。9例蹲姿最大屈膝角度由术前的76.29°~124.11°提高至术后6周的91.35°~134.12°,最大屈髋角度由术前的103.70°~147.25°提高至术后6周的118.61°~149.48°。结论:基于人工智能影像识别步态分析技术是一种安全、有效的方法可以定量识别出患者步态的变化。KOA患者在行TKA后膝关节疼痛缓解,功能得以改善,TKA术后患肢的支撑能力有所改善,患者的步频、步幅、步速得到了提升,双下肢整体运动节律更为协调。

智能化转型、组织韧性与制造业企业高质量发展

新时期制造业企业高质量发展是推动制造强国建设的重要战略环节。智能化技术与制造业的深度融合,将成为制造业企业转型升级、创新发展的历史机遇。以2012—2022沪深A股制造业企业为样本,从制造业企业智能化转型出发,探讨其对企业组织韧性和企业高质量发展的影响机制,在对三者进行量化测算的基础上进行固定效应、中介效应、异质性等实证检验。研究发现:智能化转型能够显著提升制造业企业组织韧性,并带动企业全要素生产率的提升,实现制造业企业高质量发展。经实证检验,该结论稳健。同时,智能化转型对组织韧性的提升存在地区市场化程度、企业生命周期、资本密集度、股权性质的异质性。基于此,本文从宏观层面出发,提出了政府加强顶层设计,为制造业企业的数智化转型提供配套支持及企业发挥主体作用,积极推进全过程全生命周期的智能化转型的共性建议,从中观层面出发,提出了企业可通过建立稳健的财务策略,识别并规避各种风险、优化生产流程,提高生产效率,加强供应链条稳健性建设和企业文化建设等措施提升组织韧性,以应对环境不确定性日益加剧的风险。并从微观层面建议不同性质的制造业企业应依据不同特点合理审慎做出智能化转型的战略选择,以优化资源配置效率,提高市场竞争力、加大在智能化技术和设备方面的投入,赋能价值链共生共赢,支撑企业实现韧性增长。为制造业智能化转型推动产业韧性水平、实现制造业高质量发展提供理论和现实借鉴。

数智经济推动共同富裕的机制与效应研究

共同富裕是社会主义的本质要求,数字化、智能化是引领共同富裕的重要驱动力。本文从数字化和智能化两个维度出发构建了数智经济发展水平的指标体系,并利用2012~2022年我国省际面板数据,实证分析了数智经济推动共同富裕的作用路径与影响效应。研究发现:数智经济通过提高农业全要素生产率推动共同富裕。在区域经济发达程度较低时,数智经济的发展可能会妨碍共同富裕目标的实现,但这种抑制效果将进一步削弱,直到区域经济发展达到一定水平,数智经济发展才有助于促进共同富裕。同时,数智经济发展还存在明显的空间溢出效应,可以提高邻近地区的共同富裕程度。因此,各地区应加快数智经济发展进度,使数智经济的建设更有效地服务于共同富裕目标。

育肥猪智能饮水碗设计与性能测试

饮水量及饮水的质量是影响猪只生长和健康的重要因素,研制新型猪只节水清洁型智能饮水设备对猪舍管理和提高动物福利具有重要意义。该研究对传统碗式饮水器进行了改进,研制了一种猪只智能节水型饮水碗,探究了智能饮水碗在猪只生产性能、用水量、饮水行为和碗内饮用水卫生指标方面的应用效果。试验选取100头体质量为(85.87±15.80)kg的育肥猪,随机分为2个处理组,饮水设备分别采用传统饮水碗和智能饮水碗,每个处理组5个重复,每个重复10头猪,试验期为35 d。结果表明,2种饮水碗对育肥猪的生产性能(日增质量、日采食质量和料肉比)和饮水行为(饮水次数、饮水时长)无显著影响。传统饮水碗组和智能饮水碗组育肥猪的日均用水量分别为(11.14±0.46)、(10.05±0.46)L/d,两者存在极显著差异(P<0.01);浪费水量分别为(0.89±0.13)、(0.25±0.11)L/d,两者存在极显著差异(P<0.01);育肥猪使用智能饮水碗的用水浪费率相比传统饮水碗降低了60.9%~79.5%。传统饮水碗组和智能饮水碗组育肥猪的碗内余水总大肠菌群分别为(83.00±3.46)、(68.33±4.04)MPN/100 mL,两者存在极显著差异(P<0.01)。育肥猪使用智能饮水碗的碗内余水总大肠菌群与传统饮水碗相比降低了16.3%~19.2%。该智能饮水碗能有效保障猪只饮水健康和生长需求,减少猪只饮水浪费,降低碗内余水总大肠菌群数量,提高动物福利水平。研究可为养殖场节水减排提供理论依据及技术支撑。

生产性服务数智化对农业绿色全要素生产率的影响——兼论政府环境规制的调节作用

为推进农业农村现代化,亟需以生产性服务业数智化为契机,对传统农业生产方式进行全方位改造,提高农业综合生产能力。在理论阐述农业生产性服务数智化影响农业绿色全要素生产率(AGTFP)的内在机制基础上,构建包含金融服务、科技信息服务和商贸流通服务三部分的农业生产性服务数智化综合评价指标体系,并通过回归模型对2014—2020年我国29个省(区、市)的面板数据进行实证检验。结果表明:生产性服务数智化改造对AGTFP水平的提升具有显著的促进作用。具体来讲,金融服务和商贸流通服务的数智化改造对AGTFP的影响呈现当期有效的特征,而科技信息服务数智化改造在较长的时间内仍可以保持对AGTFP的显著促进效应;农业生产性服务数智化促进作用存在明显的区域异质性,从强到弱依次为粮食主产区、粮食产销平衡区、粮食主销区;政府环境治理能够强化农业生产性服务数智化对AGTFP的影响。基于此,应大力推进现代信息技术对传统农业生产方式的改造,构建以科技信息服务为基础,金融服务、商贸流通服务为引领,拉动农业绿色全要素生产率提升的长效增长机制。

在役螺栓超声三维成像监测数据的智能化分析方法

螺栓是一种常见的机械连接件,一旦失效,可能会导致设备损坏、结构崩塌,甚至危及人身安全。因此,在役螺栓的监测一直受到广泛关注。将相控阵超声全聚焦技术应用于螺栓在役监测,开发了专用系统和阵列探头,实现了三维成像可视化监测,改变了螺栓监测数据单一的现状。针对大量三维图像化数据处理的关键问题,提出了智能化分析方法,对比分析了决策树、支持向量机和神经网络算法的适用性,最终开发了基于决策树算法的智能分析评价软件模块并取得了较好的检测效果。

基于AI三维重建技术的全髋关节置换术在成人髋关节发育不良中的疗效观察

目的:探究基于人工智能(AI)三维重建技术的全髋关节置换术(THA)治疗成人髋关节发育不良(DDH)患者的效果。方法:选取2021年4月至2023年2月我院成人DDH患者112例进行回顾性分析,根据手术方案不同进行分组,对照组的55例采取基于二维X线技术THA,观察组的57例采取基于AI三维重建技术THA。比较两组手术相关指标、术中假体与术前规划匹配情况、影像学测量参数、术前、术后1d、术后3d炎症-氧化应激指标[白介素-8(IL-8)、肿瘤坏死因子-α(TNF-α)、超氧化物歧化酶(SOD)、丙二醛(MDA)]、髋关节功能优良率及并发症发生情况。结果:观察组手术时间、术后下床活动时间、住院时间短于对照组,术中出血量少于对照组(P<0.05);观察组术中髋臼杯、股骨柄型号与术前规划匹配符合率与术后髋关节功能优良率高于对照组(P<0.05);术后1d、3d观察组血清IL-8、TNF-α、MDA水平低于对照组,SOD水平高于对照组(P<0.05);观察组双下肢长度差低于对照组(P<0.05);两组并发症总发生率比较,差异无统计学意义(P>0.05)。结论:AI三维重建技术辅助THA治疗成人DDH患者,可优化手术流程,减轻创伤应激,促进术后早期病情恢复,同时提高假体精度,减小双下肢长度差,改善髋关节功能,且有较好安全性。

人工智能技术应用与上市企业全要素生产率

新质生产力是以全要素生产率提升为标志,核心在于创新。通过爬取2008—2022年中国上市企业年报文本内容,构建人工智能技术应用程度指标,并全面检验其对企业全要素生产率的影响效应和内在机制。研究表明,人工智能技术对企业全要素生产率的驱动作用具有统计学意义。异质性检验表明,在“宽带试点”城市、“科技金融试点”城市以及数字经济发展程度较高的地区,这种驱动作用更为明显。进一步的机制检验发现,人工智能技术应用通过劳动力结构优化、投资效率改善、财务配置能力提升、创新能力升级等渠道助力企业全要素生产率提升。研究结论为政府制定人工智能应用的扶持政策和驱动企业全要生产率增加提供了新证据。

智能制造计划可以跨越“生产率悖论”吗:来自智能制造试点示范项目的准自然实验

新一代人工智能是新质生产力的典型代表和提升全要素生产率(TFP)的重要源泉。基于微观企业视角,首先对“生产率悖论”现象的出现与消失进行了一体化的理论机制阐释。随后,以我国工信部实施的智能制造试点为准自然实验,利用2011-2021年A股制造业上市公司面板数据,借助交错双重差分法实证评估了智能制造计划影响企业TFP的总效应、机制、异质性及动态影响。研究发现:(1)智能制造计划虽在短期内对企业TFP的影响不显著,但在长期和总体上提升了企业TFP;(2)机制分析表明,通过促进企业创新,智能制造计划在短期、长期和总体上均能提升企业TFP;智能制造计划在初期和总体上扭曲了企业资源配置,但这一扭曲效应随时间推移逐渐减弱,从而对企业TFP的影响呈现出U型演变特征;(3)异质性分析发现,企业人力资本结构或数字化水平越高,智能制造计划可以在总体上越大且在时序上越快地提升企业TFP。研究结果为从微观企业层面去理解“生产率悖论”现象的出现与否、内在机制、严重程度和持续时长提供了理论解释和经验证据,对探寻提升TFP的新动力源和微观机制具有政策启示意义。

人工智能对企业出口产品多元化的影响——基于中国上市公司的实证研究

本文主要采用2010—2016年中国上市公司数据库、中国海关数据库、国际机器人联合会(IFR)匹配的数据,实证研究了人工智能对企业出口产品多元化的影响,并揭示了其主要的影响机制。研究结果表明,人工智能可以显著地提高企业出口产品的多元化,在考虑了内生性、替换核心解释变量以及变换实证检验方法之后,这一结论仍旧稳健;同时这种促进作用在非国有企业、东部地区企业、劳动密集型企业与一般贸易企业中更为显著;主要的影响机制是企业生产效率提升效应和企业技术创新提高效应;在进一步的拓展研究部分,发现企业所在地区营商环境与企业数字化转型程度对人工智能的积极影响均存在正向调节效应。

人工智能对高技术产业要素配置结构效应的影响

选取2001—2021年高技术产业数据,运用增长核算模型对高技术产业要素配置的“结构红利假说”进行检验,并利用TVP-VAR模型深入探索人工智能影响高技术产业要素配置结构效应。研究发现:高技术产业全要素生产率和技术效应呈现下降变动时存在要素配置结构红利;人工智能对高技术产业要素配置结构效应存在长期正向冲击响应;人工智能对金融发展存在倒“U”型关系,人工智能对人力资本发展存在“U”型关系。两者分别为释放高技术产业资本、劳动配置结构红利的中间传导渠道,但影响时期存在差异。对此,应推进人工智能发展进程,完善金融市场监管制度,加快人力资本积累,进一步释放高技术产业要素配置结构红利,促进形成新质生产力。

全髋关节置换前人工智能(AI)规划的作用与意义

背景:传统X射线胶片术前规划常常不准确,会导致一些术中和术后并发症,增加了手术时间和术中出血量,一定程度影响了全髋关节置换的手术效果。目的:研究人工智能(AI)术前规划在全髋关节置换术中的准确性和应用效果。方法:选取患侧初次行全髋关节置换的患者60例,其中30例应用人工智能(AI)三维术前规划为试验组、30例应用传统X射线胶片二维术前规划为对照组,两组患者的性别、年龄、病情等一般资料比较,差异均无统计学意义(P>0.05)。比较两组患者术中实际安放假体与术前规划假体匹配情况、术中手术时间、术中出血量、术后即刻双侧股骨偏心距差值、双侧联合偏心距差值及双下肢长度差值和术后3个月Harris评分,分析两种术前规划的准确性和应用效果。结果与结论:①两组患者均获得术后4-6个月的随访,其中对照组有1例患者于术后5 d发生假体后脱位,行手法复位后恢复,无再次脱出,其余患者均未出现术后并发症及术后死亡;②髋臼侧、股骨侧假体完全匹配率:试验组明显优于对照组(P<0.05);③手术时间、术中出血量:试验组明显少于对照组(P<0.05);④两组患者术后双下肢长度差值比较差异有显著性意义(P<0.05),双侧股骨偏心距差值和双侧联合偏心距差值比较差异均无显著性意义(P>0.05);⑤试验组患者术后3个月Harris评分明显高于对照组患者(P<0.05);⑥结果说明,人工智能(AI)术前规划相较于传统胶片规划,更能准确预测假体型号、缩短手术时间、减少术中出血量、减少术后双下肢不等长发生、加快术后康复。