自主智能系统(英文)

Pub Date : 2026-03-10 DOI: 10.1007/s43684-026-00126-3

Jingyi Li, Rui Huang, Nan Shi, Hongjian Weng, Qiangyu Wang, Guo Li, Yufei He, Chunqi Tian

Blockchain has achieved widespread application in various fields due to its decentralized nature, data immutability, and transparency. Particularly, its integration with satellite networks provides a more secure and efficient solution for cross-regional, high-speed transmission, and reliable communication. However, challenges such as network fluctuations, performance bottlenecks, and leader election issues arise in this context, primarily due to the uneven computational power distribution of heterogeneous devices in satellite networks, as well as bandwidth limitations, signal delays, and instability. To address these challenges, this paper proposes a Dynamic Scoped Hierarchical Raft algorithm based on the network performance and computational power differences of nodes. The algorithm establishes consensus groups and restricts the pool of eligible leader candidates, thereby enhancing the adaptability of blockchain in satellite networks. Furthermore, by introducing different consensus subgroups, the scalability of the blockchain system is improved. Experimental results show that, compared to the traditional Raft algorithm, the proposed algorithm achieves a 65% increase in average throughput, a 12% reduction in latency, and a 71% reduction in leader election time, with a significantly lower chance of leader node failure when nodes drop out due to network instability.

区块链由于其去中心化、数据不变性、透明性等特点，在各个领域得到了广泛的应用。特别是与卫星网络的融合，为跨区域、高速传输、可靠通信提供了更加安全、高效的解决方案。然而，在这种情况下会出现网络波动、性能瓶颈和领导者选举等挑战，主要是由于卫星网络中异构设备的计算能力分布不均匀，以及带宽限制、信号延迟和不稳定性。为了解决这些问题，本文提出了一种基于网络性能和节点计算能力差异的动态范围分层Raft算法。该算法建立共识组，并对符合条件的leader候选者进行约束，从而增强了区块链在卫星网络中的适应性。此外，通过引入不同的共识子群，提高了区块链系统的可扩展性。实验结果表明，与传统Raft算法相比，该算法的平均吞吐量提高65%，延迟降低12%，leader选举时间减少71%，且由于网络不稳定导致节点退出导致leader节点故障的几率明显降低。

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引用次数: 0

New methods for the assessment and prediction of vector-borne infectious diseases 媒介传播传染病评估和预测的新方法

Q1 Social Sciences

Journal of Biosafety and Biosecurity

Pub Date : 2026-03-01 Epub Date: 2026-02-10 DOI: 10.1016/j.jobb.2026.01.003

Senzhong Huang , Xinyan Zhang , Xi Chen , Fengying Wei , Jianguo Xu , Yao Bai , Zhen Jin , Qiyong Liu , Yamin Sun , Jinjie Wang , Zhaojun Wang , Jun Xu , Xianming Xu , Lei Xu

This study, which demonstrates that the single-population Susceptible-Exposed-Infectious-Recovered (SEIR) model is also applicable to the assessment and prediction of vector-borne infectious disease outbreaks, provides a reliable model tool for the future prevention and control of vector-borne unknown (X) epidemics. One of the key contributions is the identification of a suitable interpretation of the model parameters. The EpiSIX prediction system, via application of a single SEIR model, was used to fit and analyse the 2025 Foshan City chikungunya fever epidemic data and the 2024–2025 dengue fever epidemics data from Guangdong Province. The results showed that the average serial interval of both fevers was approximately 11 days. The estimated basic reproduction number (R₀) was around 6.0 for the chikungunya fever epidemic in Foshan City and approximately 4.0 and 3.0 for the 2024 and 2025 dengue fever epidemics in Guangdong Province, respectively. An additional prediction of the development trend of the ongoing 2025 dengue fever epidemic in Guangdong Province indicated that the final number of infections would range between 3400 and 6000 cases. Finally, a comparison between the uncontrolled developments of the omicron epidemic (with an average serial interval of 4 days) and the chikungunya fever epidemic (with an average serial interval of 11 days, 2.75 times that of omicron) under the same R₀ value (5.60) showed that the omicron epidemic would last for 50 days, while the chikungunya fever epidemic would persist for 120 days. Theoretically, the pressure of the former on medical resources would be 2.5 times that of the latter.

本研究表明，单种群易感-暴露-感染-恢复（SEIR）模型同样适用于媒介传播传染病暴发的评估和预测，为未来预防和控制媒介传播的未知(X)流行病提供了可靠的模型工具。关键贡献之一是确定模型参数的合适解释。应用EpiSIX预测系统对2025年佛山市基孔肯雅热流行数据和广东省2024-2025年登革热流行数据进行拟合和分析。结果表明，两次发热的平均连续间隔约为11天。预计佛山市基孔肯雅热流行的基本繁殖数（R0）约为6.0，广东省2024年和2025年登革热流行的基本繁殖数（R0）分别约为4.0和3.0。对广东省2025年登革热流行发展趋势的另一项预测表明，最终感染人数将在3400至6000例之间。最后，对比相同R0值（5.60）下无控制的组粒流行（平均连续间隔4天）和基孔肯雅热流行（平均连续间隔11天，是组粒流行的2.75倍）的发展情况，发现组粒流行将持续50天，基孔肯雅热将持续120天。理论上，前者对医疗资源的压力是后者的2.5倍。

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引用次数: 0

Forecasting tuberculosis prevalence in Afghanistan until 2032: a mathematical modelling analysis 预测阿富汗到2032年的结核病流行：一个数学模型分析

Q1 Social Sciences

Journal of Biosafety and Biosecurity

Pub Date : 2026-03-01 Epub Date: 2025-12-24 DOI: 10.1016/j.jobb.2025.12.003

Abdul Raqib Muslimyar , Mohammad Farooq Hakimi , Dost Mohammad Faizi , Muhammad Haroon Stanikzai , Naqibullah Wardak

Background

Accurate disease forecasting can inform public health policies. Nonetheless, many countries, including Afghanistan, have yet to learn from this exercise.

Objectives

This study aimed to forecast tuberculosis (TB) prevalence in Afghanistan until 2032 and to estimate the reproduction number

R_{0}

using a mathematical model.

Methods

We utilised the susceptible–infected (SI) nonlinear epidemic model to forecast the prevalence of TB in Afghanistan. The model parameters were estimated from the data collected by the Afghan Ministry of Public Health between 2013 and 2022. The goodness-of-fit of the SI model was also assessed.

Results

The SI model predicted that the prevalence of TB in Afghanistan would increase to 0.214058 by 2032. In addition, we parameterised the model using the TB notification data collected between 2013 and 2022 and estimated the basic reproduction number at approximately 3.39.

Conclusion

The study indicates that the SI model predicts a nonlinear increase in TB prevalence in Afghanistan in the years ahead. Therefore, this model can help inform health policymakers in optimising resource allocation and guiding future public health strategies for TB care in the country.

准确的疾病预测可以为公共卫生政策提供信息。然而，包括阿富汗在内的许多国家尚未从这次演习中吸取教训。本研究旨在预测阿富汗到2032年的结核病（TB）患病率，并使用数学模型估计繁殖数R0。方法采用易感感染（SI）非线性流行模型对阿富汗结核病流行进行预测。模型参数是根据阿富汗公共卫生部在2013年至2022年期间收集的数据估计的。还对SI模型的拟合优度进行了评估。结果SI模型预测到2032年阿富汗结核病患病率将上升至0.214058。此外，我们使用2013年至2022年期间收集的结核病报告数据对模型进行了参数化，并估计基本复制数约为3.39。该研究表明，SI模型预测了未来几年阿富汗结核病患病率的非线性增长。因此，该模型可以帮助卫生政策制定者优化资源分配并指导该国未来的结核病治疗公共卫生战略。

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引用次数: 0

Medical students’ mobile phones: hotspots for antimicrobial-resistant Gram-negative bacteria 医学生手机：耐药革兰氏阴性菌的热点

Q1 Social Sciences

Journal of Biosafety and Biosecurity

Pub Date : 2026-03-01 Epub Date: 2025-12-24 DOI: 10.1016/j.jobb.2025.12.002

Ahmed E. Taha , Heba M. Saad Eldien , Mohamed Abouelkheir , Abdulbaqi S. Alduraywish , Ali A. Alanazi , Abdulaziz H. Alruwaili , Mmdoh M. Alrais , Abdulkareem A. Alyousef , Abdullah A. Alrais , Meshal A. Alanazi , Sultan N. Alhudaib , Bandar M. Alazmi , Abdulaziz L. Alruwaili , Gamal Abdelrahman Bakhaat

Introduction

The mobile phones (MPs) of medical personnel can be easily and rapidly contaminated by bacteria from patients or medical devices and by medical school or hospital environments. This is the first study set in Aljouf Province, Saudi Arabia, to assess the prevalence of bacterial contamination of medical students’ MPs, the antimicrobial susceptibility of the isolates and their independent risk factors.

Methodology

Swabs of 250 MPs of medical students were processed using standard microbiological procedures. Data were collected to identify independent contamination risk factors. The automated MicroScan WalkAway Microbiology System was used for bacterial isolate identification and antimicrobial sensitivity/resistance testing.

Results

The prevalence of MPs’ bacterial contamination was 56.00 % (n = 140/250). Multivariate logistic regression and stratified analyses revealed significant associations between MP bacterial contamination and a 10-minute duration since the last hand wash (odds ratio [OR] = 1.788; p = 0.037*) and the presence of breaks in the screen or screen protector of MPs (OR = 1.840; p = 0.038*). The most common bacterial contaminants were Escherichia coli, Klebsiella pneumoniae and Staphylococcus epidermidis, at frequencies of 31.79 %, 28.57 % and 19.29 %, respectively. The high frequency of Gram-negative bacterial contaminants in our geographical area was striking. Although Staphylococcus epidermidis isolates were completely sensitive, Gram-negative isolates were found to have varying degrees of reduced susceptibility to some antimicrobials.

Conclusion

Our findings support previous reports about the potential role of medical students’ MPs in the transmission of bacteria between community, medical education and healthcare (HC) settings. There is an urgent need to implement policies and regulations for MP use and decontamination, especially in medical education and HC settings. To minimise bacterial contamination risk, medical students should frequently wash their hands when in HC, medical education and community settings and ensure that their MP screens and screen protectors remain intact.

医务人员的移动电话（MPs）很容易被患者或医疗设备以及医学院或医院环境的细菌污染。这是在沙特阿拉伯Aljouf省开展的第一项研究，旨在评估医学生MPs中细菌污染的流行程度、分离物的抗菌敏感性及其独立危险因素。方法采用标准微生物程序对医学生250例MPs拭子进行处理。收集数据以确定独立的污染风险因素。采用自动MicroScan WalkAway微生物系统进行细菌分离鉴定和抗菌药物敏感性/耐药性试验。结果MPs细菌污染率为56.00% （n = 140/250）。多因素logistic回归和分层分析显示，MPs细菌污染与上次洗手后10分钟的持续时间（比值比[OR] = 1.788; p = 0.037*）和MPs的屏幕或屏幕保护膜破裂（OR = 1.840; p = 0.038*）之间存在显著关联。最常见的细菌污染物为大肠杆菌、肺炎克雷伯菌和表皮葡萄球菌，频率分别为31.79%、28.57%和19.29%。革兰氏阴性细菌污染物在我们的地理区域的高频率是惊人的。虽然表皮葡萄球菌分离株完全敏感，但革兰氏阴性分离株对某些抗菌素的敏感性有不同程度的降低。结论我们的研究结果支持了先前关于医学生MPs在社区、医学教育和卫生保健（HC）环境之间细菌传播中的潜在作用的报道。目前迫切需要实施多氯联苯使用和净化的政策和法规，特别是在医学教育和卫生保健机构。为了最大限度地降低细菌污染的风险，医学生在HC、医学教育和社区环境中应经常洗手，并确保他们的MP屏幕和屏幕保护膜完好无损。

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引用次数: 0

Patent-based analysis of biosafety trends in synthetic biology 基于专利的合成生物学生物安全趋势分析

Q1 Social Sciences

Journal of Biosafety and Biosecurity

Pub Date : 2026-03-01 Epub Date: 2026-01-30 DOI: 10.1016/j.jobb.2026.01.002

Qiangyu Xiang , Wanying Gao , Kunlan Zuo , Zongzhen Wu , Lu Zhang , Jialin Diao , Jiayun Chen , Huan Liu

This study explored biosafety trends in synthetic biology through patent analysis. As an interdisciplinary field, synthetic biology brings innovation opportunities to society, but it is accompanied by risks, such as the leakage of biological materials and genetic contamination. The Derwent Innovations Index database was used to retrieve 90 relevant patents for in-depth analysis. Through thematic term identification and data cleansing, the patent landscape and technological advancements at the intersection of synthetic biology and biosafety were assessed. Four biosafety classifications were proposed – operational biosafety, technical cell-culture limitations, pathogenic microorganism biosafety and infrastructure and facility biosafety – providing an empirical basis for relevant policymaking and practice. Quantitative analysis showed that over half of the patents were filed between 2017 and 2022 and that US patents focus mainly on operational-level safety, while Chinese patents emphasise infrastructure innovation. This study highlighted the importance of the patent literature in revealing biosafety issues in synthetic biology and suggested that these patents could be used to guide further patent applications and disclosures to promote the safe development and regulation of synthetic biology.

本研究通过专利分析探讨了合成生物学的生物安全趋势。合成生物学作为一个跨学科的领域，在给社会带来创新机遇的同时，也伴随着生物材料泄漏、基因污染等风险。使用Derwent创新指数数据库检索90项相关专利进行深入分析。通过专题术语识别和数据清理，评估了合成生物学和生物安全交叉领域的专利格局和技术进步。提出了操作生物安全、技术细胞培养限制、病原微生物生物安全、基础设施生物安全4种生物安全分类，为相关政策制定和实践提供了经验依据。定量分析显示，超过一半的专利是在2017年至2022年期间申请的，美国专利主要关注运营层面的安全，而中国专利则强调基础设施创新。本研究强调了专利文献在揭示合成生物学生物安全问题中的重要性，并建议这些专利可用于指导进一步的专利申请和披露，以促进合成生物学的安全发展和监管。

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引用次数: 0

Hepatitis B virus S gene substitutions in Iraqi patients: computational analysis of missense substitutions and functional impact 伊拉克患者乙型肝炎病毒S基因替换：错义替换和功能影响的计算分析

Q1 Social Sciences

Journal of Biosafety and Biosecurity

Pub Date : 2026-03-01 Epub Date: 2026-02-03 DOI: 10.1016/j.jobb.2026.01.001

Ahmed Yaseen Abed, Hekmat A. Owaid, Mohamad K. Koodi

Background

The hepatitis B virus (HBV) continues to be a global health concern, with immune-escape substitutions increasingly reported in regions where genotype D predominates. In Iraq, where genotype D is the dominant strain, the functional impact of naturally occurring S gene substitutions remains poorly understood. This study examined S gene substitutions in 13 chronic hepatitis B patients from Anbar Province, Iraq, and used computational approaches to assess the functional consequences of missense substitutions in the large S protein.

Methods

A 1070 bp PCR fragment covering the S gene coding regions was amplified and sequenced. Missense substitutions were analyzed using five computational prediction tools (SIFT, PolyPhen-2, PROVEAN, PhD-SNP and P-Mut). Three-dimensional modelling, protein–protein docking analysis and epitope mapping were performed for the most consistently predicted potentially disruptive substitutions.

Results

A total of 34 nucleotide substitutions were identified, including 15 missense substitutions, indicating genetic diversity among Iraqi HBV isolates from Anbar Province. Three substitutions (p.159D>A, p.126R>T and p.160P>L) were consistently predicted as functionally impactful by multiple computational tools. Protein–protein docking simulation revealed significant reductions in antibody binding affinity for p.159D>A (45%) and p.126R>T (31%), suggesting potential immune escape mechanisms. Notably, p.126R>T occurs within the vaccine-targeted ‘a’ determinant region, while p.159D>A may contribute to immune escape through predicted conformational changes despite unchanged epitope scores.

Conclusions

This in silico analysis provides an initial functional evaluation of HBV S gene substitutions in Iraqi genotype D isolates and identifies substitutions with potential implications for vaccine efficacy and immune recognition. These findings highlight the value of computational screening in resource-limited settings and underscore the need for expanded molecular surveillance and experimental validation to assess clinical significance.

乙型肝炎病毒（HBV）仍然是一个全球性的健康问题，在基因D型占主导地位的地区，免疫逃逸替代的报道越来越多。在伊拉克，基因型D是主要菌株，自然发生的S基因替换对功能的影响仍然知之甚少。本研究检测了来自伊拉克安巴尔省的13名慢性乙型肝炎患者的S基因替换，并使用计算方法评估大S蛋白错义替换的功能后果。方法扩增覆盖S基因编码区的1070 bp PCR片段并测序。用5种计算预测工具（SIFT、polyphen2、PROVEAN、PhD-SNP和P-Mut）分析错义替换。三维建模，蛋白对接分析和表位定位进行了最一致的预测潜在的破坏性取代。结果共鉴定出34个核苷酸替换，包括15个错义替换，表明安巴尔省伊拉克HBV分离株存在遗传多样性。三个替换（p.159D>；A, p.126R>；T和p.160P>；L）被多个计算工具一致地预测为功能上的影响。蛋白对接模拟显示，p.159D>；A（45%）和p.126R>；T（31%）的抗体结合亲和力显著降低，提示潜在的免疫逃逸机制。值得注意的是，p.126R>；T发生在疫苗靶向的“a”决定性区域内，而p.159D>； a可能通过预测的构象变化促进免疫逃逸，尽管表位评分不变。结论该计算机分析提供了伊拉克基因型D分离株HBV S基因替换的初步功能评估，并确定了对疫苗疗效和免疫识别具有潜在影响的替换。这些发现突出了计算筛选在资源有限的情况下的价值，并强调了扩大分子监测和实验验证以评估临床意义的必要性。

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引用次数: 0

Enhancing SS-OCT 3D image reconstruction: A real-time system with stripe artifact suppression and GPU parallel acceleration 增强SS-OCT三维图像重建：条带伪影抑制和GPU并行加速的实时系统

Q1 Computer Science

Virtual Reality Intelligent Hardware

Pub Date : 2026-02-01 Epub Date: 2026-03-14 DOI: 10.1016/j.vrih.2025.12.003

Dandan LIU

Optical coherence tomography (OCT), particularly Swept-Source OCT, is widely employed in medical diagnostics and industrial inspections owing to its high-resolution imaging capabilities. However, Swept-Source OCT 3D imaging often suffers from stripe artifacts caused by unstable light sources, system noise, and environmental interference, posing challenges to real-time processing of large-scale datasets. To address this issue, this study introduces a real-time reconstruction system that integrates stripe-artifact suppression and parallel computing using a graphics processing unit. This approach employs a frequency-domain filtering algorithm with adaptive anti-suppression parameters, dynamically adjusted through an image quality evaluation function and optimized using a convolutional neural network for complex frequency-domain feature learning. Additionally, a graphics processing unit integrated 3D reconstruction framework is developed, enhancing data processing throughput and real-time performance via a dual-queue decoupling mechanism. Experimental results demonstrate significant improvements in structural similarity (0.92), peak signal-to-noise ratio (31.62 dB), and stripe suppression ratio (15.73 dB) compared with existing methods. On the RTX 4090 platform, the proposed system achieved an end-to-end delay of 94.36 milliseconds, a frame rate of 10.3 frames per second, and a throughput of 121.5 million voxels per second, effectively suppressing artifacts while preserving image details and enhancing real-time 3D reconstruction performance.

光学相干断层扫描（OCT），特别是扫描源OCT，由于其高分辨率成像能力而广泛应用于医学诊断和工业检查。然而，扫描源OCT 3D成像经常受到不稳定光源、系统噪声和环境干扰引起的条纹伪影的影响，这给大规模数据集的实时处理带来了挑战。为了解决这个问题，本研究引入了一个实时重建系统，该系统使用图形处理单元集成了条纹伪影抑制和并行计算。该方法采用具有自适应抗抑制参数的频域滤波算法，通过图像质量评估函数动态调整，并使用卷积神经网络进行优化，用于复杂频域特征学习。此外，开发了集成三维重构框架的图形处理单元，通过双队列解耦机制提高了数据处理吞吐量和实时性。实验结果表明，与现有方法相比，该方法在结构相似度（0.92）、峰值信噪比（31.62 dB）和条纹抑制比（15.73 dB）方面均有显著提高。在RTX 4090平台上，该系统实现了94.36毫秒的端到端延迟，10.3帧/秒的帧率，1.315亿体素/秒的吞吐量，有效地抑制了伪影，同时保留了图像细节，增强了实时3D重建性能。

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引用次数: 0

Sustainable business decision modelling with blockchain and digital twins: a survey 区块链和数字孪生的可持续商业决策建模：一项调查

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2026-02-01 Epub Date: 2025-06-04 DOI: 10.1016/j.bcra.2025.100312

Gyan Wickremasinghe, Siofra Frost, Karen Rafferty, Vishal Sharma

Industry 4.0 and beyond will rely heavily on sustainable business decision modelling (BDM) that can be accelerated by blockchain and digital twin (DT) solutions. BDM is built on models and frameworks refined by key identification factors, data analysis, and mathematical or computational aspects applicable to complex business scenarios. Gaining actionable intelligence from collected data for BDM requires a carefully considered infrastructure to ensure data transparency, security, accessibility, and sustainability. Such an infrastructure must also be aligned with the social, economic, and environmental factors. A notable direct impact on BDM concerning resource optimisation, stakeholder engagement, regulatory compliance, and environmental impacts has been identified in this space. Taxonomies are defined in this paper to further understand these segments and evaluate blockchain and DT sustainability features based on an in-depth review of the current state of the art. Based on a rigorous selection procedure, 250 papers were used to evaluate the context of this study using a range of text available from scientific databases, including ACM Digital Library, IEEE Xplore, Web of Science, ScienceDirect, and Scopus. Detailed comparative evaluations provide insight into the reachability of the sustainable solution in terms of ideologies, accessibility, and performance overheads. In the context of blockchain, it is understandable that further research is required to attain practically sustainable solutions. Several questions are put forward to motivate further research that significantly impacts BDM. Finally, a case study based on an exemplary supply chain management system (SCMS) is presented to show blockchain and DT's interoperability with BDM.

工业4.0及以后将严重依赖可持续商业决策模型（BDM），而区块链和数字孪生（DT）解决方案可以加速BDM的实现。BDM建立在模型和框架之上，这些模型和框架经过关键识别因素、数据分析以及适用于复杂业务场景的数学或计算方面的改进。从BDM收集的数据中获取可操作的情报需要一个经过仔细考虑的基础设施，以确保数据的透明性、安全性、可访问性和可持续性。这样的基础设施还必须与社会、经济和环境因素保持一致。在这一领域，已经确定了对BDM在资源优化、利益相关者参与、法规遵从和环境影响方面的显著直接影响。本文定义了分类，以进一步了解这些部分，并基于对当前技术状况的深入回顾来评估区块链和DT的可持续性特征。基于严格的选择程序，250篇论文被用于评估本研究的背景，使用了一系列可从科学数据库获得的文本，包括ACM数字图书馆，IEEE Xplore, Web of Science， ScienceDirect和Scopus。详细的比较评估提供了对可持续解决方案在意识形态、可访问性和性能开销方面的可达性的洞察。在b区块链的背景下，可以理解的是，需要进一步研究以获得切实可持续的解决方案。提出了几个问题，以激励进一步的研究显著影响BDM。最后，以一个典型的供应链管理系统（SCMS）为例，展示了区块链和DT与BDM的互操作性。

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引用次数: 0

Augmented reality surgical navigation: Clinical applications, key technologies, and future directions 增强现实手术导航：临床应用、关键技术及未来发展方向

Q1 Computer Science

Virtual Reality Intelligent Hardware

Pub Date : 2026-02-01 Epub Date: 2026-03-14 DOI: 10.1016/j.vrih.2025.12.002

Yuanyuan WANG , Dawei LU , Jingfan FAN , Deqiang XIAO , Danni AI , Tianyu FU , Yucong LIN , Long SHAO , Tao CHEN , Hong SONG , Yongtian WANG , Jian YANG

Surgical navigation has evolved significantly through advances in augmented reality, virtual reality, and mixed reality, improving precision and safety across many clinical applications, including neurosurgery, maxillofacial, spinal, and arthroplasty procedures. By integrating preoperative imaging with real-time intraoperative data, these systems provide dynamic guidance, reduce radiation exposure, and minimize tissue damage. Key challenges persist, including intraoperative registration accuracy, flexible tissue deformation, respiratory compensation, and real-time imaging quality. Emerging solutions include artificial intelligence-driven segmentation, deformation-field modeling, and hybrid registration techniques. Future developments will include lightweight, portable systems, improved non-rigid registration algorithms, and greater clinical adoption. Despite advances in rigid-tissue applications, soft-tissue navigation requires additional innovation to address motion variability and registration reliability, ultimately advancing minimally invasive surgery and precision medicine.

通过增强现实、虚拟现实和混合现实的进步，外科手术导航已经有了显著的发展，提高了许多临床应用的精度和安全性，包括神经外科、颌面外科、脊柱和关节成形术。通过将术前成像与术中实时数据相结合，这些系统提供动态引导，减少辐射暴露，并最大限度地减少组织损伤。关键的挑战仍然存在，包括术中定位准确性、柔性组织变形、呼吸代偿和实时成像质量。新兴的解决方案包括人工智能驱动的分割、变形场建模和混合配准技术。未来的发展将包括轻量级、便携式系统、改进的非刚性注册算法以及更多的临床应用。尽管在硬组织应用方面取得了进展，但软组织导航需要额外的创新来解决运动变异性和注册可靠性，最终推进微创手术和精准医学。

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引用次数: 0

Unlocking the potential of data: Toward a secure and privacy-preserving blockchain-based health data governance framework 释放数据的潜力：建立一个安全和隐私保护的基于区块链的健康数据治理框架

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2026-02-01 Epub Date: 2025-06-18 DOI: 10.1016/j.bcra.2025.100318

Rita Azzi , Rima Kilany Chamoun , Ahmed Serhrouchni , Maria Sokhn

Data have always been at the heart of organizations, fueling decision-making, service delivery, and influencing people's way of life. Organizations work to improve the visibility, reliability, security, and scalability of data. Yet, these attempts are not without challenges. One of the biggest challenges faced by organizations is data confidentiality, since a data breach can affect a person's dignity with severe consequences for the organization itself. Data governance is necessary to mitigate these risks, especially when dealing with sensitive information such as health data. This research paper presents a novel approach to data governance through the development of a blockchain-based framework that aims to unlock the potential of data while minimizing the risk of data breaches and unauthorized access. It involves three critical components: data classification, data segregation, and data access control to ensure proper management, protection, and utilization of data within an organization. While this paper discusses the implementation of our framework within the healthcare ecosystem, it also offers a clear roadmap to facilitate its adoption across any data-driven domain. Our approach demonstrates how data accessibility can be enhanced while safeguarding data privacy and upholding its availability, integrity, and confidentiality.

数据一直是组织的核心，推动决策、提供服务并影响人们的生活方式。组织致力于提高数据的可见性、可靠性、安全性和可伸缩性。然而，这些尝试并非没有挑战。组织面临的最大挑战之一是数据保密，因为数据泄露可能会影响个人的尊严，并对组织本身造成严重后果。数据治理对于减轻这些风险是必要的，特别是在处理健康数据等敏感信息时。本研究报告通过开发基于区块链的框架，提出了一种新的数据治理方法，旨在释放数据的潜力，同时最大限度地降低数据泄露和未经授权访问的风险。它包括三个关键组件：数据分类、数据隔离和数据访问控制，以确保对组织内的数据进行适当的管理、保护和利用。虽然本文讨论了我们的框架在医疗保健生态系统中的实现，但它还提供了一个清晰的路线图，以促进其在任何数据驱动领域的采用。我们的方法展示了如何在保护数据隐私和维护其可用性、完整性和机密性的同时增强数据可访问性。

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