检索结果-内蒙古大学图书馆

Women in data Science at Prince Sultan University (WiDS PSU), International Conference of

作者： Juan Kenichi Sutan Jumanah Alshehri Rafaa Aljurbua Zoran Obradovic Department of Computer and Information Sciences Center for Data Analytics and Biomedical Informatics Temple University Philadelphia PA USA Department of Management Information Systems College of Business Administration Imam Abdulrahman bin Faisal University Dammam Saudi Arabia Department of Computer Science College of Computer Qassim University Buraydah Saudi Arabia

ISBN: (数字)9798331520922

ISBN: (纸本)9798331520939

Topic extraction from large text datasets is a critical task for understanding and analyzing thematic patterns across documents. This study explores three methods for improving topic modeling: standard Latent Dirichlet Allocation (LDA), a clustering-based approach combined with LDA, and an experimental method enhanced with Wikipedia-supplemented clustering. We demonstrate that applying clustering prior to LDA significantly improves topic extraction by aligning the modeling process with the natural structure of the data, allowing for the identification of smaller, yet meaningful, topics that are often overshadowed in standard LDA due to thematic imbalances. Additionally, we applied the improved topic modeling approach to construct an entity-topic network that contextualizes entities' sentiments within the topics they were mentioned in, providing a nuanced view of the dataset. Although our hypothesis that Wikipedia-enhanced clustering would further improve topic extraction was not supported, as it introduced noise and worsened performance, ClusterLDA approach proved effective in enhancing the granularity of topic extraction and addressing the limitations of standard LDA. These findings highlight the potential of clustering to support more coherent and semantically relevant topic extraction, offering a foundation for future advancements in topic modeling and sentiment analysis.

关键词： Text mining Electronic publishing Sentiment analysis Noise Encyclopedias data models Internet Online services Resource management Standards

来源：评论

学校读者我要写书评

暂无评论

Using a statewide health information exchange to Enhance COVID research and Surveillance: The impact of information fragmentation

引用

International Journal of Medical informatics 2025年

作者： Katie S. Allen Seho Park John Price Xia Ning Titus Schleyer Center for Biomedical Informatics Regenstrief Institute Inc United States Department of Industrial and Data Engineering Hongik University South Korea Biomedical Informatics Computer Science and Engineering Translational Data Analytics Institute The Ohio State University United States School of Medicine Indiana University United States

Objective Use of electronic health data for public health surveillance and research has become almost ubiquitous. However, since many patients routinely receive care from multiple healthcare systems, not all information for a patient may be available in a single system. Leveraging data from single healthcare systems may unintentionally result in inaccuracies. This study compared the variation in the number of inpatient and emergency department encounters, diagnoses, and laboratory results, as well as COVID prevalence when data about patients was (1) drawn from a single, major health system; (2) augmented with health information exchange (HIE) data; or (3) retrieved entirely from the HIE. Materials and Methods This study leveraged a registry of 1,343,703 COVID positive patients covering the state of Indiana containing data from March 6, 2020 − February 14, 2022. The data included data from the state-wide health information exchange as well as granular data from an individual health system. data elements included encounters, diagnoses, laboratory testing, and death records. Results Enhancing the cohort with data from the HIE increased the average number of encounters per person from 22.03 to 37.05, unique diagnoses from 16.06 to 30.83, and laboratory results from 0.32 to 7.06. The estimated prevalence of COVID calculated using HIE data was 22.5% higher than using data from the single system. The number of all-cause hospitalizations increased by 14% in the HIE cohort, but emergency department visits were lower in the HIE cohort by 9.4%. Conclusion Information fragmentation can lead to an incomplete picture, or even errors, in research or clinical settings. This study demonstrates that combining clinical data sources creates variation in results. Understanding the issues presented by information fragmentation, such as bias it may create, is critical to enabling more accurate disease surveillance and crisis response planning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Structured regression on multilayer networks 16

Structured regression on multilayer networks

引用

16th SIAM International Conference on data Mining 2016, SDM 2016

作者： Polychronopoulou, Athanasia Obradovic, Zoran Center for Data Analytics and Biomedical Informatics Temple University Philadelphia United States

ISBN: (纸本)9781510828117

Until recently, research in social network analysis was focused on single layer networks, where only one type of links among nodes is considered. This approach does not consider the variety of interactions that exist among nodes, resulting in the loss of a large amount of information. In the last few years there is an advanced interest in multilayer networks analysis, where multiple types of nodal connections are considered jointly. In most approaches however the contributions of the various interactions are averaged, resulting again in the loss of information. In this work we present a structured regression model for node attribute prediction in multilayer networks. Our Gaussian Conditional Random Fields model is designed to maximize the information gained from the use of data with multiple layers of graphical structure. Our model accommodates graphs with layers that share the same set of nodes allowing for missing nodes and unobserved connections. At the same time it models the evolution of such networks over time without requiring the addition of a new layer. We present evidence that this model outperforms the traditionally used one and that it offers predictive accuracy that increases as the number of layers used grows, on both synthetic data and challenging real world applications such as predicting citation count and sepsis hospitalization admission rate at all hospitals in California. Copyright © by SIAM.

关键词： Hospitals

来源：评论

学校读者我要写书评

暂无评论

Predicting poll trends using twitter and multivariate time-series classification 8th

Predicting poll trends using twitter and multivariate time-s...

引用

8th International Conference on Social informatics, SocInfo 2016

作者： Mirowski, Tom Roychoudhury, Shoumik Zhou, Fang Obradovic, Zoran Center for Data Analytics and Biomedical Informatics Temple University Philadelphia United States

ISBN: (纸本)9783319478791

Social media outlets, such as Twitter, provide invaluable information for understanding the social and political climate surrounding particular issues. Millions of people who vary in age, social class, and political beliefs come together in conversation. However, this information poses challenges to making inferences from these tweets. Using the tweets from the 2016 U.S. Presidential campaign, one main research question is addressed in this work. That is, can accurate predictions be made detecting changes in a political candidate’s poll score trends utilizing tweets created during their campaign? The novelty of this work is that we formulate the problem as a multivariate time-series classification problem, which fits the temporal nature of tweets, rather than as a traditional attribute-based classification. Features that represent various aspects of support for (or against) a candidate are tracked on an hour-by-hour basis. Together these form multivariate time-series. One commonly used approach to this problem is based on the majority voting scheme. This method assumes the univariate time-series from different features have equal importance. To alleviate this issue a weighted shapelet transformation model is proposed. Extensive experiments on over 12 million tweets between November 2015 and January 2016 related to the four primary candidates (Bernie Sanders, Hillary Clinton, Donald Trump and Ted Cruz) indicate that the multivariate time-series approach outperforms traditional attribute-based approaches. © Springer International Publishing AG 2016.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

Stay on Topic, Please: Aligning User Comments to the Content of a News Article 43rd

Stay on Topic, Please: Aligning User Comments to the Content...

引用

43rd European Conference on Information Retrieval Research, ECIR 2021

作者： Alshehri, Jumanah Stanojevic, Marija Dragut, Eduard Obradovic, Zoran Center for Data Analytics and Biomedical Informatics Temple University PhiladelphiaPA United States

ISBN: (纸本)9783030721121

Social scientists have shown that up to 50 % of the comments posted to a news article have no relation to its journalistic content. In this study we propose a classification algorithm to categorize user comments posted to a news article based on their alignment to its content. The alignment seeks to match user comments to an article based on similarity of content, entities in discussion, and topics. We propose a BERTAC, BERT-based approach that learns jointly article-comment embeddings and infers the relevance class of comments. We introduce an ordinal classification loss that penalizes the difference between the predicted and true labels. We conduct a thorough study to show influence of the proposed loss on the learning process. The results on five representative news outlets show that our approach can learn the comment class with up to 36 % average accuracy improvement comparing to the baselines, and up to 25 % comparing to the BA-BC. BA-BC is our approach that consists of two models aimed to capture dis-jointly the formal language of news articles and the informal language of comments. We also conduct a user study to evaluate human labeling performance to understand the difficulty of the classification task. The user agreement on comment-article alignment is "moderate" per Krippendorff’s alpha score, which suggests that the classification task is difficult. © 2021, Springer Nature Switzerland AG.

关键词： Alignment

来源：评论

学校读者我要写书评

暂无评论

Poster: Auto-reduction of features for containing communication costs in a distributed privacy-preserving clinical decision support system

Poster: Auto-reduction of features for containing communicat...

引用

2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2013

作者： Mathew, George Obradovic, Zoran Center for Data Analytics and Biomedical Informatics Temple University Philadelphia PA United States

ISBN: (纸本)9781479907144

The Distributed ID3-based Decision Tree (DIDT) algorithm provides a basis for Distributed Privacy-preserving Clinical Decision Support Systems. Due to large number of features associated with clinical patient records and iterative nature of distributed algorithms, exchanging information related to all features is expensive. We show that auto-reduction for features can be achieved with significant improvement in communication costs. Auto-reduction was implemented in DIDT and results of experiments using Nationwide Inpatient Sample data sets for 2008 are presented. © 2013 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Distributed privacy preserving decision support system for predicting hospitalization risk in hospitals with insufficient data

Distributed privacy preserving decision support system for p...

引用

11th IEEE International Conference on Machine Learning and Applications, ICMLA 2012

作者： Mathew, George Obradovic, Zoran Center for Data Analytics and Biomedical Informatics Temple University Philadelphia PA United States

ISBN: (纸本)9780769549132

Building prediction models for suggestive knowledge from multiple sources dynamically is of great interest from a clinical decision support point of view. This is valuable in situations where the local clinical data repository does not have sufficient number of records to draw conclusions from. However, due to privacy concerns, hospitals are reluctant to divulge patient records. Consequently, a distributed model building mechanism that can use just the statistics from multiple hospitals' databases is valuable. Our DIDT algorithm builds a model in that fashion. In this study, using National Inpatient Sample (NIS) data for 2009, we demonstrate that DIDT algorithm can be used to help collaboratively build a better decision-making model in situations where hospitals have small number of records that are insufficient to make good local models. Based on 262 attributes used for model building, we showed that 9 collaborating hospitals each with less than 100 cases of hospitalizations related to diabetes were able to achieve 9.9% improvement in accuracies of hospitalization prediction collectively using a distributed model as compared to relying on local models developed on their own. When relying on local risk prediction models for diabetes at these 9 hospitals, 159 of 357 patients were misclassified and prediction was impossible for another 16 patients. Our integrated model reduced the misclassification to 138 effectively providing accurate early diagnostics to 37 additional patients. We also introduce the concept of banding to improve DIDT algorithm so as to logically combine multiple hospitals when large number of hospitals is involved for reduction in cross-validation folds. © 2012 IEEE.

关键词： Hospitals

来源：评论

学校读者我要写书评

暂无评论

Constraint graphs as security filters for privacy assurance in medical transactions 11

Constraint graphs as security filters for privacy assurance ...

引用

2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM-BCB 2011

作者： Mathew, George Obradovic, Zoran Center for Data Analytics and Biomedical Informatics Temple University Philadelphia PA United States

ISBN: (纸本)9781450307963

We model transactions as exchange of graphs and propose constraint graphs as transaction filters for attribute-based transformations in clinical settings. An informal representation and working of constraint graphs is presented. A workbench was developed using a real world EMR system to demonstrate the concept. Results of our experiments using constraint graphs are consistent with published benchmark results. Copyright © 2011 ACM.

关键词： Medical informatics

来源：评论

学校读者我要写书评

暂无评论

Autonomous Navigation for Drone Swarms in GPS-Denied Environments Using Structured Learning 16th

Autonomous Navigation for Drone Swarms in GPS-Denied Environ...

引用

16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020

作者： Power, William Pavlovski, Martin Saranovic, Daniel Stojkovic, Ivan Obradovic, Zoran Center for Data Analytics and Biomedical Informatics Temple University PhiladelphiaPA United States

ISBN: (纸本)9783030491857

Drone swarms are becoming a new tool for many tasks including surveillance, search, rescue, construction, and defense related activities. As their usage increases, so does the possibility of adversarial attacks on their contribution to these use cases. One possible avenue, whether deliberate or not, is to deny access to the position feedback offered by the Global Positioning System (GPS). Operating in these ‘GPS denied’ environments poses a new challenge;both in navigation, and in collision avoidance. This study proposes two novel concepts;a structural model of environmental deviance to aid in autonomous navigation, and a method to use the output of said model to implement a collision avoidance system. Both of these concepts are developed and tested in the framework of a simulated environment that mimics a GPS-denied scenario. Using data from hundreds of simulated swarm flights, this work shows structured learning can improve navigational accuracy without the need for externally provided position feedback. © 2020, IFIP International Federation for Information Processing.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

A phenome-wide association study of uterine fibroids reveals a marked burden of comorbidities

Communications Medicine

引用

Communications Medicine 2025年第1期5卷 174页

作者： Jasper, Elizabeth A. Mautz, Brian S. Hellwege, Jacklyn N. Piekos, Jacqueline A. Jones, Sarah H. Zhang, Yanfei Torstenson, Eric S. Pendergrass, Sarah A. Lee, Ming Ta Michael Edwards, Todd L. Velez Edwards, Digna R. Division of Quantitative and Clinical Sciences Department of Obstetrics and Gynecology Vanderbilt University Medical Center Nashville TN United States Center for Precision Medicine Vanderbilt University Medical Center Nashville TN United States Institute for Medicine and Public Health Vanderbilt University Medical Center Nashville TN United States Vanderbilt Epidemiology Center Vanderbilt University Nashville TN United States Vanderbilt Genetics Institute Vanderbilt University Nashville TN United States Population Analytics Analytics & Insights Data Sciences Janssen Research & Development Spring House PA United States Division of Genetic Medicine Department of Medicine Vanderbilt University Medical Center Nashville TN United States Genomic Medicine Institute Geisinger Health Systems Danville PA United States Department of Biomedical Informatics Vanderbilt University Medical Center Nashville TN United States Division of Epidemiology Department of Medicine Vanderbilt University Medical Center Nashville TN United States Genentech South San Francisco CA United States Department of Biomedical and Translational Informatics Geisinger Rockville MD United States

Background: The burden of comorbidities in those with uterine fibroids compared to those without fibroids is understudied. We performed a phenome-wide association study to systematically assess the association between fibroids and other conditions. Methods: Vanderbilt University Medical center’s Synthetic Derivative and Geisinger Health System database, two electronic health record databases, were used for discovery and validation. Non-Hispanic Black and White females were included. Fibroid cases were identified through a previously validated algorithm. Race-stratified and multi-population phenome-wide association analyses, adjusting for age and body mass index, were performed before statistically significant, validated results were meta-analyzed. Results: There were 52,295 and 26,918 (9022 and 10,232 fibroid cases) females included in discovery and validation analyses. In multi-population meta-analysis, 389 conditions were associated with fibroid risk, with evidence of enrichment of circulatory, dermatologic, genitourinary, musculoskeletal, and sense organ conditions. The strongest associations within and across racial groups included conditions previously associated with fibroids. Numerous novel diagnoses, including cancers in female genital organs, were tied to fibroid status. Conclusions: Overall, individuals with fibroids have a marked increase in comorbidities compared to those without fibroids. This approach to evaluate the health context of fibroids highlights the potential to understand fibroid etiology through studying the common biology of comorbid diagnoses and through disease networks. © The Author(s) 2025.

关键词：

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：