检索结果-内蒙古大学图书馆

A computational Pipeline for Patient-Specific Prediction of the Post-operative Mitral Valve Functional State 1

Functional Imaging and modeling of the Heart - 12th International Conference, FIMH 2023, Proceedings

作者： Liu, Hao Simonian, Natalie T. Pouch, Alison M. Gorman, III, Joseph H. Gorman, Robert C. Sacks, Michael S. James T. Willerson Center for Cardiovascular Modeling and Simulation The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering The University of Texas at Austin AustinTX78712 United States Departments of Radiology and Bioengineering University of Pennsylvania PhiladelphiaPA19104 United States Gorman Cardiovascular Research Group Department of Surgery Smilow Center for Translational Research Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States

ISBN: (数字)9783031353024

ISBN: (纸本)9783031353017

Mitral valve (MV) repair is safer than replacement for mitral regurgitation (MR) treatment, but long-term outcomes remain suboptimal and poorly understood. Moreover, preoperative optimization is complicated due to the heterogeneity of MR presentations and potential repair configurations. We thus developed a patient-specific MV computational pipeline to quantitatively predict the post-repair MV functional state using standard-of-care preoperative imaging data alone. First, we built a finite-element model of the full patient-specific MV apparatus by quantifying the MV chordae tendinae (MVCT) distributions from 5 CT-imaged excised human hearts and incorporating this data with patient-specific MV leaflet geometries and and MVCT origin displacements from preoperative 3D echocardiography. We then calibrated the leaflet and MVCT pre-strains by simulating preoperative MV closure in order to tune the functionally equivalent, patient-specific mechanical behavior. With this fully calibrated MV model, we simulated undersized ring annuloplasty (URA) by modifying the annular displacement to match the applied ring size. In all patient cases, the postoperative geometries were predicted to within 1 mm of the target, and the MV leaflet strain fields demonstrated very good global and local correspondence to results from a previous heavily validated pipeline. Additionally, our model predicted increased postoperative posterior leaflet tethering in a recurrent patient, which is the likely driver of long-term MV repair failure. This pipeline allows us to predict postoperative outcomes using strictly preoperative clinical data, which lays the foundation for quantitative surgical planning, personalized patient selection, and ultimately, more durable MV repairs. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Echocardiography

来源：评论

学校读者我要写书评

暂无评论

CMM PLN at MentalRiskES: A Traditional Machine Learning Approach for Detection of Eating Disorders and Depression in Chat Messages

CMM PLN at MentalRiskES: A Traditional Machine Learning Appr...

引用

2023 Iberian Languages Evaluation Forum, IberLEF 2023

作者： Guerra, Rodrigo Pizarro, Benjamín Muñoz-Castro, Carlos Carvallo, Andrés Rojas, Matías Aracena, Claudio Dunstan, Jocelyn Center for Mathematical Modeling Universidad de Chile Chile Faculty of Physical and Mathematical Sciences Universidad de Chile Chile Department of Computer Science Pontificia Universidad Católica de Chile Santiago Chile National Center for Artificial Intelligence Chile Institute for Mathematical and Computational Engineering Pontificia Universidad Católica de Chile Chile Millenium Institute Foundational Research on Data Chile

This paper describes our approaches to solving the MentalRiskES task, which belongs to the IberLEF (Iberian Languages Evaluation Forum) shared task. The task aims to identify the eating disorders and depression of a user using a series of Telegram messages. Our proposed system uses the traditional TFiDF method to represent the messages and then utilizes these representations as input for machine learning models. The best results for classification were obtained using the Naive Bayes classifier, while in the regression task, the best models were Gradient Boots Regressor and Linear Regressor. Despite its simplicity, we demonstrated that our traditional approaches can still achieve competitive results in recent NLP tasks, obtaining the best results in the case of detecting depression and eating disorders. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Conceptual Development of a Probabilistic Graphical Framework for Assessing Port Resilience 23rd

Conceptual Development of a Probabilistic Graphical Framewor...

引用

23rd International Conference on Harbor, Maritime and Multimodal Logistics Modelling and simulation, HMS 2021

作者： Smith, Katherine Diaz, Rafael Shen, Yuzhong Longo, Francesco Virginia Modeling Analysis & Simulation Center Old Dominion University 1030 University Blvd SuffolkVA23435 United States Department of Computational Modeling and Simulation Engineering Old Dominion University 1300 Engineering & Computational Sciences Building NorfolkVA23529 United States Mechanical Department University of Calabria Via Pietro Bucci Arcavacata CS Rende87036 Italy

ISBN: (纸本)9788885741591

Technological advances such as cyber physical systems and autonomous vehicles combined with increased disruptions including the Covid-19 pandemic and coastal natural disasters have heightened the importance of port risk analysis methodologies and frameworks that can accurately quantify and optimize resilience. This work presents the conceptual development of a novel combination of analysis methodologies linking a probabilistic graphic approach on a network of risk events with a functional dependency approach on a system network. Key advantages of these two methodologies are the ability to model and learn causal interactions rather than simply correlations and a high level of computational efficiency. This combination of robustness and flexibility offers the ability to quickly analyze multiple port configurations in order to invest in efforts that maximize the resilience-cost ratio. In addition, the methodology opens the door for real-time anomaly detection and causal analysis in order to enhance efforts in the protecting against attacks on infrastructure and in particular cyber physical systems. © 2021 The Authors.

关键词： Cyber Physical System

来源：评论

学校读者我要写书评

暂无评论

Matrix Stiffness Regulates Mechanotransduction and Vascular Network Formation of Hipsc-Derived Endothelial Progenitors Encapsulated in 3d Hydrogels

SSRN

引用

SSRN 2025年

作者： Han, Jiwan Halwachs, Kathleen West, Toni Larsen, Bryce Sacks, Michael S. Rosales, Adrianne M. Zoldan, Janet Department of Biomedical Engineering The University of Texas at Austin AustinTX United States Department of Chemical Engineering The University of Texas at Austin AustinTX United States James T. Willerson Center for Cardiovascular Modeling and Simulation The Oden Institute for Computational Engineering and Sciences AustinTX United States

The mechanical properties of the extracellular matrix (ECM), particularly stiffness, regulate endothelial progenitor responses during vascular development, yet their behavior in physiologically compliant matrices (10 kPa), our results emphasize that vascularization is not solely driven by the most mechanotransductive environment but rather by a balance of compliance, contractility, and cell-induced remodeling. These findings underscore the need to design hydrogels that provide sufficient mechanotransduction for endothelial maturation while maintaining compliance to support dynamic vascular morphogenesis. This work provides a mechanically tuned framework for optimizing microenvironments to balance endothelial differentiation and vascular network formation in tissue engineering and regenerative medicine. © 2025, The Authors. All rights reserved.

关键词： Endothelial cells

来源：评论

学校读者我要写书评

暂无评论

Projection of China’s future runoff based on the CMIP6 mid-high warming scenarios

引用

Science China Earth sciences 2023年第3期66卷 528-546页

作者： Jiayue ZHOU Hui LU Kun YANG Ruijie JIANG Yuan YANG Wei WANG Xuejun ZHANG Department of Earth System Science Ministry of Education Key Laboratory of Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China National Tibetan Plateau Data Center State Key Laboratory of Tibetan Plateau Earth System and Resource EnvironmentInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China Center for Western Weather and Water Extremes Scripps Institution of OceanographyUniversity of California San DiegoSan Diego 92037USA Changjiang Institute of Survey PlanningDesign and ResearchWuhan 430010China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower ResearchBeijing 100038China Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources Beijing 100038China

The latest Coupled Model Intercomparison Project Phase 6(CMIP6)proposes new shared pathways(SSPs)that incorporate socioeconomic development with more comprehensive and scientific experimental designs;however,few studies have been performed on the projection of future multibasin hydrological changes in China based on CMIP6 *** this paper,we use the Equidistant Cumulative Distribution Function method(EDCDFm)to perform downscaling and bias correction in daily precipitation,daily maximum temperature,and daily minimum temperature for six CMIP6 models based on the historical gridded data from the high-resolution China Meteorological Forcing dataset(CMFD).We use the bias-corrected precipitation,temperature,and daily mean wind speed to drive the variable infiltration capacity(VIC)hydrological model,and study the changes in multiyear average annual precipitation,annual evapotranspiration and total annual runoff depth relative to the historical baseline period(1985–2014)for the Chinese mainland,basins and grid scales in the 21st century future under the SSP2-4.5 and SSP5-8.5 *** study shows that the VIC model accurately simulates runoff in major Chinese basins;the model data accuracy improves substantially after downscaling bias correction;and the future multimodel-mean multiyear average annual precipitation,annual evapotranspiration,and total annual runoff depth for the Chinese mainland and each basin increase relative to the historical period in near future(2020–2049)and far future(2070–2099)under the SSP2-4.5 and *** new CMIP6-based results of this paper can provide a strong reference for extreme event prevention,water resource utilization and management in China in the 21st century.

关键词： CMIP6 VIC model EDCDFm Chinese basins Future hydrological changes

来源：评论

学校读者我要写书评

暂无评论

Multinomial belief networks for healthcare data

arXiv

引用

arXiv 2023年

作者： Donker, Hylke C. Neijzen, D. de Jong, J. Lunter, G.A. Department of Epidemiology University Medical Center Groningen Groningen Netherlands Statistical Modeling Global Computational Biology and Data Sciences Boehringer Ingelheim Pharma GmbH & Co. KG Biberach an der Riß Germany

Healthcare data from patient or population cohorts are often characterized by sparsity, high missingness and relatively small sample sizes. In addition, being able to quantify uncertainty is often important in a medical context. To address these analytical requirements we propose a deep generative Bayesian model for multinomial count data. We develop a collapsed Gibbs sampling procedure that takes advantage of a series of augmentation relations, inspired by the Zhou–Cong–Chen model. We visualise the model’s ability to identify coherent substructures in the data using a dataset of handwritten digits. We then apply it to a large experimental dataset of DNA mutations in cancer and show that we can identify biologically meaningful clusters of mutational signatures in a fully data-driven way. © 2023, CC BY.

关键词： Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

High-Speed simulation of the 3D Behavior of Myocardium Using a Neural Network PDE Approach 11th

High-Speed Simulation of the 3D Behavior of Myocardium Using...

引用

11th International Conference on Functional Imaging and modeling of the Heart, FIMH 2021

作者： Zhang, Wenbo Li, David S. Bui-Thanh, Tan Sacks, Michael S. Willerson Center for Cardiovascular Modeling and Simulation Oden Institute for Computational Engineering and Sciences Department of Biomedical Engineering University of Texas at Austin AustinTX78712 United States Oden Institute for Computational Engineering and Sciences Department of Aerospace Engineering and Engineering Mechanics University of Texas at Austin AustinTX78712 United States

ISBN: (纸本)9783030787097

The full characterization of three-dimensional (3D) mechanical behaviour of myocardium is essential in understanding their function in health and disease. The hierarchical structure of myocardium results in their highly anisotropic mechanical behaviors, with the spatial variations in fiber structure giving rise to heterogeneity. The optimal set of loading paths has been used to estimate the constitutive parameters of myocardium using a novel numerical-experimental approach with full 3D kinematically controlled (triaxial) experiments [1, 2]. Due to the natural variations in soft tissue structures, the mechanical behaviors of myocardium can vary dramatically within the same organ. To alleviate the associated computational costs for obtaining responses of myocardium under a range of loading conditions with a given realization of structure, we developed a neural network-based method integrated with finite elements. The boundary conditions were parameterized. The neural network generated a corresponding trial solution of the underling hyperelasticity problem for each boundary condition. Thus, the neural network approximated the parameter-to-state map. A physics-informed approach was used to train the neural network. Due to their learnability characteristics, the neural network was able to predict solutions for a range of boundary conditions with given individual specimen fiber structures. The neural network was validated with finite element solutions. This method will provide efficient and robust computational models for clinical evaluation to improve patient outcomes. © 2021, Springer Nature Switzerland AG.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Multirate Time-Integration based on Dynamic ODE Partitioning through Adaptively Refined Meshes for Compressible Fluid Dynamics

arXiv

引用

arXiv 2024年

作者： Doehring, Daniel Schlottke-Lakemper, Michael Gassner, Gregor J. Torrilhon, Manuel Applied and Computational Mathematics RWTH Aachen University Schinkelstrasse 2 North Rhine-Westphalia Aachen52062 Germany University of Stuttgart Germany High-Performance Scientific Computing Center for Advanced Analytics and Predictive Sciences University of Augsburg Germany Department of Mathematics and Computer Science Center for Data and Simulation Science University of Cologne Germany

In this paper, we apply the Paired-Explicit Runge-Kutta (P-ERK) schemes by Vermeire et. al. [1, 2] to dynamically partitioned systems arising from adaptive mesh refinement. The PERK schemes enable multirate time-integration with no changes in the spatial discretization methodology, making them readily implementable in existing codes that employ a method-of-lines approach. We show that speedup compared to a range of state of the art Runge-Kutta methods can be realized, despite additional overhead due to the dynamic re-assignment of flagging variables and restricting nonlinear stability properties. The effectiveness of the approach is demonstrated for a range of simulation setups for viscous and inviscid convection-dominated compressible flows for which we provide a reproducibility repository. In addition, we perform a thorough investigation of the nonlinear stability properties of the Paired-Explicit Runge-Kutta schemes regarding limitations due to the violation of monotonicity properties of the underlying spatial discretization. Furthermore, we present a novel approach for estimating the relevant eigenvalues of large Jacobians required for the optimization of stability *** Codes 65L06, 65M20, 76Mxx, 76Nxx © 2024, CC BY.

关键词： Runge Kutta methods

来源：评论

学校读者我要写书评

暂无评论

Securing the light escaping in a Li-Fi network environment

引用

Procedia Computer Science 2022年 201卷 684-689页

作者： D.D. Diambeki R.E. Mandiya K. Kyamakya S.K. Kasereka University of Kinshasa Mathematics and Computer Science Department Kinshasa DR Congo Artificial intelligence Big data and modeLing simulation research center (ABIL) Kinshasa Democratic Republic of the Congo Alpen-Adria-Universitaet Klagenfurt Institute of Smart Systems Technologies Department of Mathematical Sciences Klagenfurt Austria

Nowadays, everyone knows Wi-Fi. The technology that ensures connection of computer equipment. It is now positioned as the easiest way to interconnect multiple end users because It allows user mobility in workspaces, avoids cable clutter within the network coverage, such as offices, homes and so on. Despite these advantages, several scientific studies have shown that this technology can raise security and safety issues and is dangerous to human health, and therefore not suitable for hospital networks. In an attempt to overcome these difficulties, Li-Fi technology based on visible light is beginning to interest researchers. This technology is considered more secure than Wi-Fi because the light can be contained in a physical space and waves can’t pass through walls and other objects. Unfortunately, when the physical environment contains spaces that can escape light to the outdoors, this can be a security risk for Li-Fi because it uses light sources to transmit data. That why, in this paper, the main differences between Wi-Fi and Li-Fi technologies are explained, and a Li-Fi architecture provided with an authentification captive portal and a data transfer security mechanism between end users based on the AES algorithm is proposed. The developed prototype and the architecture proposed guarantee the security of the Li-Fi network even if the physical environment is provided with multiple light escape spaces.

关键词： Li-Fi (Light-Fidelity) VLC (Visible Light Communication) LED (Light Emitting Diode) Photodetector LDR (Light Dependent Resistor) Arduino AES algorithm Captive portal

来源：评论

学校读者我要写书评

暂无评论

Biomedical data and AI

引用

Science China(Life sciences) 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences(CLS) Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China Center for Quantitative Biology(CQB) Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China Department of Physics University of ChicagoChicagoIL 60637USA School of Life Sciences Southern University of Science and TechnologyShenzhen 518055China Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies Chengdu 610213China College of Chemistry and Molecular Engineering Peking UniversityBeijing 100871China Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu 610041China Department of Biology Massachusetts Institute of TechnologyCambridgeMA 02139USA Lambic Therapeutics Inc.San DiegoCA 92121USA Changping Laboratory Beijing 102200China Al for Science Institute Beijing 100083China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan UniversityShanghai 200433China Department of Obstetrics and Gynecology West China Second University HospitalSichuan UniversityChengdu 610041China Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking UniversityBeijing 100871China Channing Division of Network Medicine Department of MedicineBrigham and Women’s Hospital and Harvard Medical SchoolBostonMA 02115USA Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-ChampaignUrbanaIL 61801USA Department of Genetics and Genome Scien

The development of artificial intelligence(AI)and the mining of biomedical data complement each *** the direct use of computer vision results to analyze medical images for disease screening,to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries,the boundaries of both are constantly expanding,and their connections are becoming ***,the theme of the 2024 Annual Quantitative Biology Conference is set as“Biomedical data and AI”,and was held in Chengdu,China from July 15 to 17,2024.

关键词： biomedical data mining biomedical data computer vision artificial intelligence artificial intelligence ai integrating biological knowledge models disease screeningto quantitative biology conference

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：