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CHDbase:A Comprehensive knowledgebase for Congenital Heart Disease-related Genes and Clinical Manifestations

Genomics, Proteomics & Bioinformatics 2023年第1期21卷 216-227页

作者： Wei-Zhen Zhou Wenke Li Huayan Shen Ruby W.Wang Wen Chen Yujing Zhang Qingyi Zeng Hao Wang Meng Yuan Ziyi Zeng Jinhui Cui Chuan-Yun Li Fred Y.Ye Zhou Zhou State Key Laboratory of Cardiovascular Disease Beijing Key Laboratory for Molecular Diagnostics of Cardiovascular DiseasesCenter of Laboratory MedicineFuwai HospitalNational Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100037China International Joint Informatics Laboratory&Jiangsu Key Laboratory of Data Engineering and Knowledge Service School of Information ManagementNanjing UniversityNanjing 210023China Institute of Molecular Medicine Peking UniversityBeijing 100871China

Congenital heart disease(CHD)is one of the most common causes of major birth defects,with a prevalence of 1%.Although an increasing number of studies have reported the etiology of CHD,the findings scattered throughout the literature are difficult to retrieve and utilize in research and clinical *** therefore developed CHDbase,an evidence-based knowledgebase of CHD-related genes and clinical manifestations manually curated from 1114 publications,linking 1124 susceptibility genes and 3591 variations to more than 300 CHD types and related *** such as the information of each publication and the selected population and samples,the strategy of studies,and the major findings of studies were integrated with each item of the research *** also integrated functional annotations through parsing50 databases/tools to facilitate the interpretation of these genes and variations in disease *** further prioritized the significance of these CHD-related genes with a gene interaction network approach and extracted a core CHD sub-network with 163 *** clear genetic landscape of CHD enables the phenotype classification based on the shared genetic ***,CHDbase provides a comprehensive and freely available resource to study CHD susceptibilities,supporting a wide range of users in the scientific and medical *** is accessible at http://***.

关键词： Congenital heart disease Congenital heart defect database Genetics Classification

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Gender Disparity in Expressed Emotions within Health-Related Online Support Groups

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Proceedings of the Association for Information Science and Technology 2021年第1期58卷 883-885页

作者： Zhao, Yuehua Wang, Hao Deng, Sanhong Chen, Ye Nanjing University Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing China Central China Normal University Wuhan China

Online support groups offer a new way to users to communicate with others regarding certain health issues. Taking autism-related support groups on Facebook as an example, we examine whether the expressed emotions differ between female and male users in online health-related support groups and whether such gender disparity varied based on the topics of the groups. Experimental results reveal a significant gender difference of expressed emotions in the groups. We find that female users tended to express more positive emotions in the group discussions than the male group members did. In addition, users appeared to express different sentiments within the groups focused on various topics. Male users tend to convey more negative emotions in the group that related to treatment, while female users were more positive when posted in the research-related group than male users were. This study is beneficial for tracking and moderating the emotional environment in online support groups. 84 Annual Meeting of the Association for Information Science & Technology | Oct. 29 – Nov. 3, 2021 | Salt Lake City, UT. Author(s) retain copyright, but ASIS&T receives an exclusive publication license.

关键词： Sentiment analysis

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Identifying Scientific and Technical“Unicorns”

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Journal of data and Information Science 2021年第2期6卷 96-115页

作者： Lucy L.Xu Miao Qi Fred Y.Ye Jiangsu Key Laboratory of Data Engineering and Knowledge Service School of Information ManagementNanjing UniversityNanjing 210023China University Library Nantong UniversityNantong 226019China

Purpose:Using the metaphor of"unicorn,"we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing,which may provide a new pattern to understand very high impact works in science and ***/methodology/approach:When we set CT as the total citations of papers or patents in the first ten years after publication,with CT≥5,000 for scientific"unicorn"and CT≥500 for technical"unicorn,"we have an absolute standard for identifying scientific and technical"unicorn"***:We identify 165 scientific"unicorns"in 14,301,875 WoS papers and 224 technical"unicorns"in 13,728,950 DII patents during 2001–*** 50%of"unicorns"belong to biomedicine,in which selected cases are individually *** rare"unicorns"increase following linear model,the fitting data show 95%confidence with the RMSE of scientific"unicorn"is 0.2127 while the RMSE of technical"unicorn"is *** limitations:A"unicorn"is a pure quantitative consideration without concerning its quality,and"potential unicorns"as CT≤5,000 for papers and CT≤500 for patents are left in future *** implications:Scientific and technical"unicorns"provide a new pattern to understand high-impact works in science and ***"unicorn"pattern supplies a concise approach to identify very high-impact scientific papers and technical ***/value:The"unicorn"pattern supplies a concise approach to identify very high impact scientific papers and technical patents.

关键词： Unicorn Scientific paper Technical patent Citation analysis Patent analysis

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Evaluating the Performance to Detecting Topic Shift of Large Language Models: A Study 9

Evaluating the Performance to Detecting Topic Shift of Large...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Tian, Pingfang Liu, Deting Department of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Institute of Scientific and Technical Information of China The Key Laboratory of the Rich Media Knowledge Organisation and Service of Digital Publishing Content Beijing100038 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan430065 China

ISBN: (纸本)9798350376548

Topic shift detection aims to identify whether there is a change in the current topic of conversation or if a change is needed. The study found previous work did not evaluate the performance of large language models like ChatGPT on the task of topic shift. Therefore, this paper's main task and innovation lie in analyzing ChatGPT's performance on topic shift detection. To provide a more comprehensive evaluation, we conducted topic shift detection tasks on ChatGPT from three aspects: single utterances, adjacent utterances, and contextual levels. Additionally, to gauge the performance of large language models, we conducted experiments on multiple small-scale models and compared the results of the two models. Experimental results on the publicly available English TIAGE dataset showed that small-scale models exhibited lower recall in all three aspects, while ChatGPT performed better in the recall. This suggests that compared to small-scale models, large models are more capable of accurately detecting topic shifts. However, large models also exhibited lower precision, indicating that while ChatGPT can recognize content differences in utterances, its judgment on whether these different contents belong to the same topic is poor. © 2024 IEEE.

关键词： adjacent utterances level ChatGPT contextual level single utterances level topic shift detection

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A Semantic Framework for Chinese Historical Events Based on Linked data and knowledge Graph 16th

A Semantic Framework for Chinese Historical Events Based on ...

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16th International Conference on Diversity, Divergence, Dialogue, iConference 2021

作者： Wang, Hao Li, Yueyan Deng, Sanhong School of Information Management Nanjing University Nanjing210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China

ISBN: (纸本)9783030712914

In the era of big data, data redundancy has become an obstacle to deep reading. The objective of linked data as a new data organization model is to transform data into structured data following unified standards. The lack of Chinese conceptual terms has seriously hindered the semantization and standardization of Chinese domain ontology. Taking Chinese historical events as an example, ontology technology is used in this paper to standardize the definition of concepts and semantic relations in domain knowledge. Moreover, concepts from text resources are extracted through a deep learning algorithm Bi-LSTM-CRFs and combined with an external knowledge base to realize the fusion of related data within various data sets. Ultimately, the knowledge ontology of historical events is displayed in the way of a knowledge graph to further explore the practical application. The results show that the accuracy of the terms extraction of historical events is about 80% indicating the good recognition performance and portability of the model. © 2021, Springer Nature Switzerland AG.

关键词： Linked data

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Detecting the research diversity of researchers in library and information science:An exploratory study

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data Science and Informetrics 2022年第3期2卷 22-36页

作者： Yuehua Zhao Sicheng Zhu Jie Wu Hao Wang Sanhong Deng Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing UniversityNanjingChina School of Information Management Nanjing UniversityNanjingChina

Metrics have emerged as an important tool for quantitatively evaluating researchers from a variety of perspectives,including research impact,research quality,interdisciplinarity,and *** in the field of library and information science,many previous studies have highlighted the characteristics of researchers in this ***,only a minority of the studies address the aspect of diversity in research *** purpose of this study is to(1)evaluate the topic diversity of researchers in library and information science and(2)examine the relationships between the researcher topic diversity and research *** propose an indicator to quantify author topic diversity,which we refer to as author topic diversity(ATD).Latent Dirichlet Allocation(LDA)is used to detect topics in the field,while cosine similarity is used to calculate the diversity of research topics in a given researcher’s *** results show that topic diversity in the field of library and information science varies greatly from author to *** addition,weak positive correlations are found between the ATD and citation indicators,suggesting that engaging in diversified topics may lead to higher research impact.

关键词： Research diversity Research evaluation Library and information science

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An Empirical Study on the Tourism Image of Nanjing from the Perspective of International Students 7th

An Empirical Study on the Tourism Image of Nanjing from the ...

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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Han, Pu Zhang, Mingtao Yao, Mingxiu Hui, Zhenrong Chen, Meitong School of Management Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Provincial Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China

ISBN: (纸本)9783030786175

International students are a special group in Chinese cities, and their tourism image perception has important research significance for urban tourism construction. Based on the destination tourism image model proposed by Baloglu and McCleary, the tourism image of Nanjing is divided into three aspects: cognitive image, emotional image and overall image. Aiming at the international student group in Nanjing, the questionnaire survey was used to obtain the perception data of the group’s tourism image in Nanjing with SPSS. The empirical research on the tourism image of Nanjing was carried out from three aspects: tourism image perception factor, overall image perception and representative attractions. The study found that in the structured part of the dimension, international students are most satisfied with "urban environment" and least concerned about "attractions". Through the single factor measurement, the most satisfied one is the rich historical and cultural heritage, and the most dissatisfied one is the crowded urban environment. In the unstructured part of the international students on Nanjing tourism image, the overall satisfaction is high, in which the destination image perception of the "delicious food" is the best. In the perception of urban tourism image, the perception of "a beautiful city" is the best. The analysis of the characteristics of social population structure shows obvious individualized difference. Boys tend to Zhongshan mausoleum, and girls are more inclined to Confucius Temple Qinhuai scenery belt. © 2021, Springer Nature Switzerland AG.

关键词： Surveys

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Fake News Detection Based on Personality Prediction Model

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data Analysis and knowledge Discovery 2025年第4期9卷 123-133页

作者： Wu, Qi Yu, Wei Chen, Junpeng Key Laboratory of Data Engineering and Knowledge Service in Jiangsu Province Nanjing University Nanjing210023 China School of Computer and Artificial Intelligence Nanjing University of Finance & Economics Nanjing210046 China

[Objective] This paper aims to improve the efficiency of fake news detection by mining personality information from comment text. [Methods] BERT models learn the textual features of news and comments. The personality prediction model based on BERT model training learns the big five personality traits. The text features and personality traits of news and comments are used to predict true and fake news. [Results] The experiment is conducted on a subset of Weibo datasets. The result shows that the addition of personality traits could improve the accuracy of fake news detection (+1.96%,90.76%) and F1 scores (+1.51%,90.60%). [Limitations] The use of a personality prediction model requires a certain number of comment texts. The interpretability of the model needs to be further improved. [Conclusions] The personality traits of comment users can effectively improve the identification accuracy and F1 values of fake news detection. © 2025 Chinese Academy of Sciences. All rights reserved.

关键词： Big Five Personality Traits Fake News Detection Personality Prediction Model Pre-training Model

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Salient Patch Based NAS for Grading of Colorectal Cancer Histology Images 13

Salient Patch Based NAS for Grading of Colorectal Cancer His...

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13th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2022

作者： Meng, Hang Li, Fei Yang, Zhen Zhu, Qiang Fan, Chaogang Zhan, Shu Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology Anhui Province Hefei230009 China The Second Affiliated Hospital of Anhui Medical University Anhui Province Hefei230601 China Tongcheng Teachers College Anhui Province Tongcheng231400 China Department of General Surgery The Affiliated BenQ Hospital of Nanjing Medical University Jiangsu Province Nanjing210021 China

ISBN: (纸本)9781950492619

Digital histopathological tissue images are gold material for cancer diagnosis and grades. Convolutional Neural Networks (CNNs) are state-of-the-art models in many image classification tasks. However, considering the limited computing resources, it is not practical to directly train CNNs on gigapixel resolution histopathological tissue images. Therefore, the entire histopathological image is commonly divided into a grid of patches and then fed each patch to CNNs, but not all patches are necessary for specific tasks. Besides, although CNNs are excellent image classifiers, many pre-trained models are based on natural images. Neural Architecture Search (NAS) can realize automatic search, construction, and training specific problemoriented networks. We present salient patch based NAS for grading colorectal cancer (CRC) histology images with these motivations. The proposed framework first applies the classic classification network to extract significant patches from the whole image, then use the network obtained by NAS to grade the patches, and finally aggregates the patch-level predictions to generate the entire CRC histological image label. Our experiments on microscopic colorectal tissue images demonstrate that the proposed method is sufficient to obtain more accurate classification results compared to its counterparts. We also conducted a comprehensive analysis of the different scenarios of the proposed method. © by the International Institute of Informatics and Systemics.

关键词： Grading

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Unveiling Funded Research: Impact and Dual Innovation

SSRN

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SSRN 2023年

作者： Yang, Alex Jie School of Information Management Nanjing University Nanjing210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China International Joint Informatics Laboratory Nanjing University Nanjing210023 China

In the relentless pursuit of scientific advancement, comprehending the profound impact and innovation nature inherent in funded research projects assumes paramount significance. To illuminate this matter, I delve into the realm of research supported by the esteemed National Institutes of Health (NIH) and the distinguished National Science Foundation (NSF). Our evaluative framework encompasses a spectrum of metrics, including the 5-year citation, normalized citation, and citation to patents, as markers of research impact. Moreover, I embrace ex-ante innovation (Novelty) and ex-post innovation (Disruption) as dual indispensable yardsticks for evaluating the innovative nature of research projects. Novelty denotes the manifestation of atypical combinations of existing knowledge, while Disruption signifies the extent of paradigm-shifting potential and the ability to exert a disruptive influence on future research endeavors. First, the analysis reveals that funded research projects manifest a conspicuously heightened impact in comparison to their non-funded counterparts. Second, I uncover a noteworthy finding, namely that funded research demonstrates significantly higher levels of ex-ante innovation (Novelty). However, in a surprising twist, the investigation also uncovers that funded research exhibits significantly lower levels of ex-post innovation (Disruption). Additionally, I undertake a meticulous scrutiny of the robustness of the research findings by scrutinizing patterns across disparate years and fields. This comprehensive analysis further unveils inconspicuous heterogeneity, thus substantiating the multifaceted nature of funded research and the vast potential for its innovation across various disciplines and temporal dimensions. © 2023, The Authors. All rights reserved.

关键词： Patents and inventions

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