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在线医疗健康服务医患信任影响因素实证研究

管理科学 2017年第1期30卷 43-52页

作者：邓朝华洪紫映华中科技大学医药卫生管理学院武汉430030

在线医疗健康服务作为线下医疗健康服务的补充对缓解医疗资源相对不足等问题有着重要的意义,而信任作为人际关系的基石对在线的医患关系有深刻影响,因此有必要研究在线医疗健康服务中的医患信任问题。有诸多因素影响医患信任,医患信任... 详细信息

在线医疗健康服务作为线下医疗健康服务的补充对缓解医疗资源相对不足等问题有着重要的意义,而信任作为人际关系的基石对在线的医患关系有深刻影响,因此有必要研究在线医疗健康服务中的医患信任问题。有诸多因素影响医患信任,医患信任的提升对患者的行为意向也有积极影响。以在线医患信任为核心,重点从患者角度研究在线医疗健康网站中医患信任的影响因素,分析个人、网站、医院和医生4个方面的影响。同时,感知风险和感知收益从宏观上也会影响在线患者信任和患者行为意向,也将其纳入分析。基于此,以信任模型的概念框架以及感知风险和感知收益等理论为基础构建模型,提出9个假设。以有在线医疗健康网站中服务经验的用户为研究对象,使用问卷调查的方法进行调研,获得271份有效样本,利用结构方程模型的实证方法对研究假设进行检验。研究结果表明,除个人信任倾向外,医患信任影响因素中的网站、医院和医生的可信度均对在线患者信任有显著影响,其中网站因素的影响程度最高,在线患者信任也显著影响患者行为意向。感知收益和感知风险对在线患者信任也有显著影响,但对患者行为意向的影响不显著。将医患信任的研究从线下延伸至线上,探讨在线患者信任的影响因素。研究结果为研究在线医疗健康服务中的患者信任提供理论依据,同时为在线医疗健康服务的发展提供参考策略。

关键词：医疗健康网站医患信任感知风险感知收益行为意向

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在线医疗健康网站患者信任转移研究

中华医院管理杂志 2018年第9期34卷 735-739页

作者：洪紫映姚亚男邓朝华华中科技大学同济医学院医药卫生管理学院武汉430030

目的利用方程模型研究患者在医疗健康网站中信任转移的影响因素和作用机制。方法以群体趋同效应和医患交互行为等理论为基础，构建信任转移模型。采用在线抓取数据的方法，从“好大夫在线”网站中抓取2017年5月1日至2017年11月30日的在... 详细信息

目的利用方程模型研究患者在医疗健康网站中信任转移的影响因素和作用机制。方法以群体趋同效应和医患交互行为等理论为基础，构建信任转移模型。采用在线抓取数据的方法，从“好大夫在线”网站中抓取2017年5月1日至2017年11月30日的在线咨询记录。共获取225条医生记录，用多元回归方法进行实证分析。结果患者的线上信任对其在线下就诊时的医生信任有正向影响，回归系数为0．94，在***的水平下显著。患者激励、群体规模和群体互动频率，是患者线上信任的重要影响因素；患者激励、群体规模以及患者线上努力等，都对患者线下信任有显著作用。结论患者线上信任是影响其线下信任的重要因素之一。在线健康网站的开发者可从激励和互动等角度提高患者的线上信任水平，营造良好的就医环境，促进其对线下医生的信任，提高就医满意度。

关键词：信息服务患者信任信任转移在线医疗健康网站

“互联网+ ”背景下医疗行业信息安全策略探讨

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医学信息学杂志 2022年第2期43卷 62-67页

作者：陈心怡吴翔洪紫映华中科技大学同济医学院医药卫生管理学院武汉430030

针对“互联网+”背景下医疗行业存在的信息安全和隐私保护问题,结合中美两国在医疗信息安全方面有关政策和法律法规,探讨我国医疗行业信息安全未来发展方向并提出建议。

关键词： “互联网+” 健康信息管理信息安全政策研究

Deep Reinforcement Learning-Based Computation Offloading for 5G Vehicle-Aware Multi-Access Edge Computing Network

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China Communications 2021年第11期18卷 26-41页

作者： ziying Wu Danfeng Yan State Key Laboratory of Network and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

Multi-access Edge Computing(MEC)is one of the key technologies of the future 5G *** deploying edge computing centers at the edge of wireless access network,the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application ***,with the development of IOV(Internet of Vehicles)technology,various delay-sensitive and compute-intensive in-vehicle applications continue to *** with traditional Internet business,these computation tasks have higher processing priority and lower delay *** this paper,we design a 5G-based vehicle-aware Multi-access Edge Computing network(VAMECN)and propose a joint optimization problem of minimizing total system *** view of the problem,a deep reinforcement learningbased joint computation offloading and task migration optimization(JCOTM)algorithm is proposed,considering the influences of multiple factors such as concurrent multiple computation tasks,system computing resources distribution,and network communication ***,the mixed integer nonlinear programming problem is described as a Markov Decision *** show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption,optimize computing offloading and resource allocation schemes,and improve system resource utilization,compared with other computing offloading policies.

关键词： multi-access edge computing computation offloading 5G vehicle-aware deep reinforcement learning deep q-network

Take precautions against potential threats that carbon nanotubes may bring to you

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Science China Chemistry 2020年第2期63卷 141-142页

作者： Min Luo ziying Xiang Zhanjun Gu CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China College of Materials Science and Optoelectronic Technology University of Chinese Academy of SciencesBeijing 100049China

Long-term pulmonary exposure to multi-walled carbon nanotubes (MWCNTs) may promote breast cancer metastasis and rapid colonization in the lungs and other organs according to recent research conducted by *** Chen,*** Z... 详细信息

关键词： carbon potential organs

Uranium Potential and Regional Metallogeny in China

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Acta Geologica Sinica(English Edition) 2008年第4期82卷 741-744页

作者： ZHANG Jindai LI ziying Bureau of Geology China National Nuclear Corporation （CNNC） Beijing 100013 China Beijing Research Institute of Uranium Geology CNNC Beijing 100029 China

This paper is briefly involved in distributions of China＇s uranium metallogenic types, provinces, regions and belts. Eight target regions have been pointed out to be worthy of prospecting for uranium resources. The regional uranium metallogeny is discussed and great uranium potential pointed out from many aspects. Generally speaking, there are favorable conditions for uranium mineralization and good perspective to explore for uranium resources.

关键词： uranium regional metallogeny resource potential China

Functional hair follicle regeneration:an updated review

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Signal Transduction and Targeted Therapy 2021年第3期6卷 723-733页

作者： Shuaifei Ji ziying Zhu Xiaoyan Sun Xiaobing Fu Research Center for Tissue Repair and Regeneration affiliated to the Medical Innovation Research Department and 4th Medical Center PLA General Hospital and PLA Medical CollegePLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin InjuryRepair and RegenerationResearch Unit of Trauma CareTissue Repair and RegenerationChinese Academy of Medical Sciences2019RU051Beijing 100048People's Republic of China

The hair follicle(HF)is a highly conserved sensory organ associated with the immune response against pathogens,thermoregulation,sebum production,angiogenesis,neurogenesis and wound *** recent advances in lineage-tracing techniques and the ability to profile gene expression in small populations of cells have increased the understanding of how stem cells operate during hair growth and regeneration,the construction of functional follicles with cycling activity is still a great challenge for the hair research field and for translational and clinical *** that hair formation and cycling rely on tightly coordinated epithelial-mesenchymal interactions,we thus review potential cell sources with HF-inducive capacities and summarize current bioengineering strategies for HF regeneration with functional restoration.

关键词： healing wound hair

Nuclear Power Development for Greenhouse Gas Emission Reduction in China

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Advances in Climate Change Research 2011年第2期2卷 75-78页

作者： ziying Jiang China Institute of Atomic Energy Beijing 102413 China

It is a consensus of international community to promote the development of low carbon economy in order to face the challenges of climate change. According to the features of nuclear energy, the greenhouse gas （GHG） emission of nuclear energy chain and other energy chain are compared and analyzed, and the results indicate that the GHG emission of nuclear power chain is the least in all types of power generation. The status of nuclear power development and the potential benefit in GHGs emission reduction by developing nuclear power in China are also analyzed. Active nuclear power development is a smart choice for constructing low-carbon energy structure and for addressing global climate changes in China.

关键词： nuclear power GHG emission climate change

Image Generation of Tomato Leaf Disease Identification Based on Small-ACGAN

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Computers, Materials & Continua 2023年第7期76卷 175-194页

作者： Huaxin Zhou ziying Fang Yilin Wang Mengjun Tong School of Mathematics and Computer Science Zhejiang A&F UniversityHangzhou311300China Zhejiang Provincial Key Laboratory of Forestry Intelligent Monitoring and Information Technology Research Hangzhou311300China School of Humanities and Law Zhejiang A&F UniversityHangzhou311300China Department of Computer Science and Engineering Lehigh UniversityPA18015USA

Plant diseases have become a challenging threat in the agricultural *** learning approaches for plant disease detection and classification have been adopted to detect and diagnose these diseases ***,deep learning entails extensive data for training,and it may be challenging to collect plant *** though plant datasets can be collected,they may be uneven in *** a result,the problem of classification model overfitting *** study targets this issue and proposes an auxiliary classifier GAN(small-ACGAN)model based on a small number of datasets to extend the available ***,after comparing various attention mechanisms,this paper chose to add the lightweight Coordinate Attention(CA)to the generator module of Auxiliary Classifier GANs(ACGAN)to improve the image ***,a gradient penalty mechanism was added to the loss function to improve the training stability of the *** show that the proposed method can best improve the recognition accuracy of the classifier with the doubled *** AlexNet,the accuracy was increased by 11.2%.In addition,small-ACGAN outperformed the other three GANs used in the ***,the experimental accuracy,precision,recall,and F1 scores of the five convolutional neural network(CNN)classifiers on the enhanced dataset improved by an average of 3.74%,3.48%,3.74%,and 3.80%compared to the original ***,the accuracy of MobileNetV3 reached 97.9%,which fully demonstrated the feasibility of this *** general experimental results indicate that the method proposed in this paper provides a new dataset expansion method for effectively improving the identification accuracy and can play an essential role in expanding the dataset of the sparse number of plant diseases.

关键词： Deep learning ACGAN CA gradient penalty tomato diseases identification