检索结果-内蒙古大学图书馆

8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Huang, Yu-Ju Tseng, Yi-Shiou Chen, Tzu-Jung Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Surgery Far Eastern Memorial Hospital Graduate Institute of Medicine Yuan Ze University Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Kidney stones are primarily crystals formed from ion oversaturation in urine. Currently, the diagnosis of kidney stones involves experienced professionals manually interpreting images of urinary crystals under a microscope. In recent years, with the rapid development of artificial intelligence (AI), many researchers have proposed various methods to assist in diagnosis, hoping to improve medical quality. This study explored the application of AI in the medical field, aiming to automate the interpretation of urinary crystal images, such as red blood corpuscles (RBCs), calcium oxalate monohydrate (COM), calcium oxalate dihydrate octahedron (COD-OCT), calcium oxalate dihydrate dodecahedron (COD-DOD), debris, and others, and to use image processing techniques to classify urinary crystal types. This research is expected to assist medical personnel in quickly determining the categories of urinary crystals. Ultimately, our model achieved an F1-score of 0.93, indicating that this architecture has significant potential. © 2024 Copyright ACM.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Base on GAN Combined with CNN Architecture to Generate Brain Stroke CT Images 24

Base on GAN Combined with CNN Architecture to Generate Brain...

引用

8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Shih, Guan-Yu Ting, Hsien-Wei Chen, Yi-Xiang Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Graduate Program inBiomedical Informatics Yuan Ze University Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare New Taipei City242 Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

In recent years, many fields have expanded their research methods through the integration of artificial intelligence. In the current medical field, it is widely used in image recognition to diagnose patient symptoms, train clinical prediction models, and improve clinical workflow processes to avoid missing treatment opportunities. These methods have all achieved good results so far. Now, generative AI is also impacting the development of the medical field, not only generating prescriptions that match patient conditions but also being applied in generating medical images for data augmentation and simulating various pathological conditions, thereby aiding in training deep learning models. Stroke is a leading cause of death or disability, ranking as the second leading cause of death worldwide, next to cancer. If cancers were categorized individually, stroke would surpass all single diseases, making it a primary focus of research in brain disease treatment. There are already studies where generative AI has been used to create medical images, which are then manually evaluated by doctors to determine if they were generated by AI. In this project, we plan to generate CT images of strokes using generative AI and use a trained model (to diagnose stroke) to improve accuracy. Through this project, we hope to solve the problem of scarce stroke CT images while also providing support for training stroke-related models. © 2024 Copyright ACM.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Correction: Learning distribution-free anchored linear structural equation models in the presence of measurement error

引用

Journal of the Korean Statistical Society 2025年 1-2页

作者： Chung, Junhyoung Ahn, Youngmin Shin, Donguk Park, Gunwoong Department of Statistics Seoul National University Seoul Republic of Korea Institute for Data Innovation in Science Seoul National University Donguk Shin Seoul Republic of Korea Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Republic of Korea

来源：评论

学校读者我要写书评

暂无评论

Implementation Challenge of Artificial Intelligence in Human Resource Management for Employee Performance Monitoring Indonesia Companies Perspective

Implementation Challenge of Artificial Intelligence in Human...

引用

International Conference on ICT For Smart Society (ICISS)

作者： Edi Yusuf Wirawan Merios Gusan Putra Budi Nugroho Doctoral Program of Management Brawijaya University Jakarta Campus Indonesia Doctoral Program of Information Systen Diponegoro University Semarang Indonesia Program of Information System STMIK TAZKIA Bogor Indonesia Res. Center for Data and Information Science National Research and Innovation Agency Bandung Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

The main problem solved is to Improve Employee Performance Monitoring by Integrating Artificial Intelligence (AI) in Human Resource Management for Indonesian Companies. The paper suggests using AI technologies to analyze and process employee performance data. The overarching goal of this new approach is to identify patterns and red flags at the individual and team levels that can be used to inform stronger performance management strategies such as guided coaching, pointed feedback, or calibrated evaluations. This study is written as a schematic literature review, using sourced research articles from Indonesia and other countries to obtain the effects of AI on employee performance. This exercise showed how AI works in performance patterns and assists HR strategies. The findings AI has an impact on recognizing patterns in empirical data of how employees perform, helps to tailor training/development programs, and improves talent management and succession planning. Those results signify that AI has the potential to be a game-changer for HR practices in Indonesia. AI in HRM using employee performance monitoring seems an encouraging alternative for Indonesia. Through data-driven decision-making and automated HR routine tasks with many challenges and should prepare well to implement.

关键词： Leadership Smart cities Employment Ecosystems Decision making Companies Planning Pattern recognition Artificial intelligence Monitoring

来源：评论

学校读者我要写书评

暂无评论

Exome-wide variation in a diverse barley panel reveals genetic associations with ten agronomic traits in Eastern landraces

引用

Journal of Genetics and Genomics 2023年第4期50卷 241-252页

作者： June-Sik Kim Kotaro Takahagi Komaki Inoue Minami Shimizu Yukiko Uehara-Yamaguchi Asaka Kanatani Daisuke Saisho Ryuei Nishii Alexander ELipka Takashi Hirayama Kazuhiro Sato Keiichi Mochida Bioproductivity Informatics Research Team RIKEN Center for Sustainable Resource ScienceYokohama 230-0045Japan Institute of Plant Science and Resources Okayama UniversityKurashiki 710-0046Japan Kihara Institute for Biological Research Yokohama City UniversityYokohama 244-0813Japan Graduate School of Nanobioscience Yokohama City UniversityYokohama 236-0027Japan School of Information and Data Sciences Nagasaki UniversityNagasaki 852-8521Japan Department of Crop Sciences University of IllinoisUrbanaIL 61801USA Microalgae Production Control Technology Laboratory RIKEN Baton Zone ProgramRIKEN Cluster for ScienceTechnology and Innovation HubYokohama 230-0045Japan

Barley(Hordeum vulgare ***)is one of the first crops to be domesticated and is adapted to a wide range of *** barley germplasm collections possess valuable allelic variations that could further improve barley *** barley genomics has offered a global picture of allelic variation among varieties and its association with various agronomic traits,polymorphisms from East Asian varieties remain *** this study,we analyze exome polymorphisms in a panel of 274 barley varieties collected worldwide,including 137 varieties from East Asian countries and *** reveal the underlying population structure and conduct genome-wide association studies for 10 agronomic ***,we examin genome-wide associations for traits related to grain size such as awn length and glume *** results demonstrate the value of diverse barley germplasm panels containing Eastern varieties,highlighting their distinct genomic signatures relative to Western subpopulations.

关键词： Barley Exome-seq Genome-wide association study(GWAS) Population structure Allelic variation

来源：评论

学校读者我要写书评

暂无评论

Development of Automated Detection Methods for Calculating Blood Vessel Width and Stenosis Rate in Cardiac Catheterization Imaging 24

Development of Automated Detection Methods for Calculating B...

引用

8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Huang, Hsien-Cheng Chang, Hsiao-Huang Ke, Xiang-Wei Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Cardiovascular Surgery Department Taipei Veterans General Hospital Taipei City Taiwan Taipei Medical University Taipei City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Coronary artery disease is the most prevalent type of heart disease and has a considerable mortality rate. In diagnosing and assessing coronary artery disease, physicians must integrate a variety of clinical information and test results to evaluate the degree of coronary artery obstruction and continually learn and improve their skills in clinical practice to ensure the most accurate assessment of patients. Currently, the use of information technology to assist medical staff allows more effective and accurate analysis of symptoms. This approach not only serves as an auxiliary standard for physician diagnosis, thereby reducing the possibility of misdiagnosis, but also significantly improves patient treatment outcomes and medical quality while reducing the time burden on physicians for diagnosing patients. This study utilized image processing techniques and thinning algorithms to automate the detection of coronary artery width and, following the recommended methods of physicians in related fields, used specific vessel widths to calculate the degree of coronary artery narrowing. This provides a more accurate and efficient assessment method for evaluating the degree of vascular constriction in patients with coronary artery disease. © 2024 Copyright ACM.

关键词： Patient treatment

来源：评论

学校读者我要写书评

暂无评论

SynHING: Synthetic Heterogeneous Information Network Generation for Graph Learning and Explanation

arXiv

引用

arXiv 2024年

作者： Hong, Ming-Yi Huang, Yi-Hsiang Lin, Shao-En Teng, You-Chen Wang, Chih-Yu Lin, Che Graduate Program of Data Science National Taiwan University Academia Sinica Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Research Center for Information Technology Innovation Academia Sinica Taiwan

Graph Neural Networks (GNNs) excel in delineating graph structures in diverse domains, including community analysis and recommendation systems. As the interpretation of GNNs becomes increasingly important, the demand for robust baselines and expansive graph datasets is accentuated, particularly in the context of Heterogeneous Information Networks (HIN). Addressing this, we introduce SynHING, a novel framework for Synthetic Heterogeneous Information Network Generation aimed at enhancing graph learning and explanation. SynHING systematically identifies major motifs in a target HIN and employs a bottom-up generation process with intra-cluster and inter-cluster merge modules. This process, supplemented by post-pruning techniques, ensures the synthetic HIN closely mirrors the original graph’s structural and statistical properties. Crucially, SynHING provides ground-truth motifs for evaluating GNN explainer models, setting a new standard for explainable, synthetic HIN generation and contributing to the advancement of interpretable machine learning in complex networks. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

SARA: Semantic-assisted Reinforced Active Learning for Entity Alignment

SARA: Semantic-assisted Reinforced Active Learning for Entit...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Ching-Hsuan Liu Chih-Ming Chen Jing-Kai Lou Ming-Feng Tsai Jiun-Lang Huang Chuan-Ju Wang Data Science Degree Program National Taiwan University Academia Sinica Taiwan Research Center for Information Technology Innovation Academia Sinica KKCompany Taiwan Department of Computer Science National Chengchi University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Research Center for Information Technology Innovation Academia Sinica Taiwan

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

This paper introduces SARA, a semantic-assisted reinforced active learning framework for enhancing entity alignment (EA) under limited supervision scenarios. SARA addresses the challenges of EA in real-world scenarios, including knowledge graph heterogeneity and limited training ground truth. SARA effectively selects valuable entity pairs with limited labeled data by combining reinforced active learning and semantic information. It utilizes a pair-wise language model based on Sentence-BERT to learn informative name embeddings that capture entity name semantics. These embeddings are combined with structural embeddings and trained using a novel semantic-assisted alignment loss. Extensive experiments on benchmark datasets and a real-world dataset demonstrate the superiority of SARA over existing approaches, particularly in limited labeled data scenarios. The paper also provides insights into fine-tuning strategies, presents ablation studies, and conducts sensitivity analyses to validate the effectiveness of SARA.

关键词： Training Sensitivity analysis Semantics Neural networks Knowledge graphs Benchmark testing data models

来源：评论

学校读者我要写书评

暂无评论

SRECG: ECG Signal Super-Resolution Framework for Portable/Wearable Devices in Cardiac Arrhythmias Classification

引用

IEEE Transactions on Consumer Electronics 2023年第3期69卷 250-260页

作者： Chen, Tsai-Min Tsai, Yuan-Hong Tseng, Huan-Hsin Liu, Kai-Chun Chen, Jhih-Yu Huang, Chih-Han Li, Guo-Yuan Shen, Chun-Yen Tsao, Yu National Taiwan University and Academia Sinica Graduate Program of Data Science Taipei106319 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei115 Taiwan Taiwan Artificial Intelligence Academy Foundation Program of Taiwan AI Academy New Taipei22065 Taiwan Artificial Intelligence Foundation Technology Development Center New Taipei24158 Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei10617 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei115 Taiwan National Taiwan University Department of Mathematics Taipei10617 Taiwan

A combination of cloud-based deep learning (DL) algorithms with portable/wearable (P/W) devices has been developed as a smart heath care system to support automatic cardiac arrhythmias (CAs) classification using electrocardiography (ECG). However, long-term and continuous ECG monitoring is challenging because of limitations of batteries and transmission bandwidth of P/W devices while incorporated with consumer electronics (CE). A feasible approach to address this challenge is to decrease sampling rates. However, low sampling rates lead to low-resolution signals that hinder the CAs classification performance. In this study, we propose a DL-based ECG signal super-resolution framework (called SRECG) to enhance low-resolution ECG signals by jointly considering the accuracies when applied to the DL-based high-resolution multiclass classifier (HMC) of CAs. In our experiments, we downsampled the ECG signals from the CPSC2018 dataset and evaluated their HMC accuracies with and without the SRECG. Experimental results show that SRECG can well improve the HMC accuracies as compared to traditional interpolation methods. Moreover, approximately half of the CAs classification accuracies of HMC were maintained within the enhanced ECG signals by SRECG. The promising results confirm that SRECG can be suitably used to enhance low-resolution ECG signals from P/W devices with CE to improve their cloud-based HMC performances. © 1975-2011 IEEE.

关键词： Electrocardiography

来源：评论

学校读者我要写书评

暂无评论

THE EFFECT OF VISUAL APPEAL, SOCIAL INTERACTION, ENJOYMENT, AND COMPETITION ON MOBILE ESPORTS ACCEPTANCE BY URBAN CITIZENS

引用

Interdisciplinary Journal of Information, Knowledge, and Management 2022年 17卷 601-624页

作者： Wilis, Nufri Manik, Lindung Parningotan Computer Science Graduate Program University of Nusa Mandiri Jakarta Indonesia Research Center for Data and Information Sciences National Research and Innovation Agency Bandung Indonesia

Aim/Purpose This study investigated a model of mobile esports acceptance among urban citizens based on an extended Technology Acceptance Model (TAM). Background Currently, esports are increasingly popular and in demand by the public. Supported by the widespread development of mobile devices, it has become an interactive market trend to play games in a new model, mobile esports. Methodology This study collected data from 400 respondents and analyzed it using partial least squares-structural equation modeling (PLS-SEM). Contribution This study addresses two research gaps. The first gap is limited esports information systems studies, particularly in mobile esports acceptance studies. The second gap is limited exploration of external variables in online gaming acceptance studies. Thus, this study proposed a TAM extended model by integrating the TAM native variables with other external variables such as visual appeal, enjoyment, social interaction, and competition to explore mobile esports acceptance by urban citizens. Findings Nine hypotheses were accepted, and four were rejected. The visual appeal did not affect the acceptance. Meanwhile, social interaction and enjoyment significantly affected both perceived ease of use and usefulness. However, perceived ease of use surprisingly had an insignificant effect on attitude toward using mobile esports. Moreover, competition significantly affected the acceptance, particularly on perceived usefulness. Recommendations Fresh and innovative features, such as new game items or themes, should be frefor Practitioners quently introduced to enhance players’ continued enjoyment. Moreover, mobile esports providers should offer a solid platform to excite players’ interactions to increase the likelihood that users feel content. On the other hand, the national sports ministry/agency or responsible authorities should organize many esports competitions, big or small, to search for new talents. Recommendations Visual appeal in this study did

关键词： Social networking (online)

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：