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Enhanced Performance and Data Privacy in Lung Nodule Classification via Federated Deep Learning Approach 24

Enhanced Performance and Data Privacy in Lung Nodule Classif...

引用

2024 7th International Conference on Healthcare Service management, ICHSM 2024

作者： Nguyen, Duc-Khanh Li, Ai-Hsien Adam Lai, Yen-Jun Chiu, Yen-Ling Phan, Dinh-Van Chien, Ting-Ying Chan, Chien-Lung Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Statistics and Informatics University of Economics The University of Danang Danang Viet Nam Division of Cardiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan ZDT Group- YZU Joint Research and Development Center for Big Data Taoyuan Taiwan Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400710162

This study explores the feasibility of deep learning for classifying nodule neoplasms, analyzing their performance on two openly available datasets, LUNGx SPIE, and LIDC-IDRI. These datasets offer valuable diversity in image quantity, quality, and malignancy annotation methodologies, posing a real-world challenge for effective model development. To handle the disparities in these diverse datasets, we aim to develop a robust classification model trained using federated learning. This decentralized approach allows model training across datasets without sharing patient data, preserving privacy and overcoming data fragmentation. Our experiments demonstrate that federated learning enables the development of a robust and superior deep learning model compared to individual models trained on limited data. This combination of deep learning, and federated learning holds immense promise for nodule neoplasm classification and can significantly improve patient care and outcomes. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

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Deriving financial aid optimization models from admissions data

Deriving financial aid optimization models from admissions d...

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37th ASEE/IEEE Frontiers in Education Conference, FIE

作者： Van Thanh, Le Haddawy, Peter Asian Institute of Technology Computer Science and Information Management Program

ISBN: (纸本)1424410843

This paper presents a novel approach to deriving probabilistic models that predict enrollment given applicant background and the amount of financial aid offered. Our Bayesian network models can be used to optimize various enrollment objectives. We present a novel efficient optimization algorithm that uses the models to maximize expected tuition revenue under capacity constraints including student-faculty ratio and accommodation. We demonstrate and evaluate our approach using four years of graduate admissions data from the Asian Institute of Technology, consisting of 7,788 applicants from 84 different countries. This data set is particularly challenging since reliable family income data is not available for students from most of these countries. Evaluating the Bayesian network model with 10-fold cross validation yields an ROC Az value of 0.8451, with a predictive accuracy of 82.70% at a threshold of 0.5. Comparing the results of the tuition revenue optimization model to the institute's current financial aid allocation practice shows that if single-term tuition revenue is the sole optimization criterion, the institute can achieve its current enrollment numbers while realizing significant savings in its financial aid budget. The prediction and optimization software is currently being incorporated into the institute's online admissions processing system. ©2007 IEEE.

关键词： Bayesian networks

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Expanding the plausible solution space for robustness in an intelligent tutoring system

Expanding the plausible solution space for robustness in an ...

引用

9th International Conference on Intelligent Tutoring Systems

作者： Kazi, Hameedullah Haddawy, Peter Suebnukarn, Siriwan Computer Science and Information Management Program Asian Institute of Technology Thailand School of Dentistry Thammasat University Thailand Department of Computer Science Isra University Pakistan

ISBN: (纸本)9783540691303

The knowledge acquisition bottleneck is a problem pertinent to the authoring of any intelligent tutoring system. Allowing students a broad scope of reasoning and solution representation whereby a wide range of plausible student solutions are accepted by the system, places additional burden on knowledge acquisition. In this paper we present a strategy to alleviate the burden of knowledge acquisition for building a tutoring system for medical problem-based learning (PBL). The Unified Medical Language System (UMLS) is deployed as domain ontology and information structure in the ontology is exploited to make intelligent inferences and expand the domain model. Using these inferences and expanded domain model, the tutoring system is able to accept a broader range of plausible student solutions that lie beyond the scope of explicitly encoded solutions. We describe the development of a tutoring system prototype and report the evaluation of system correctness in accepting such plausible solutions. The system evaluation indicates an average accuracy of 94.59% when compared against human domain experts, who agreed among themselves with a statistical agreement based on Pearson Correlation Coefficient of 0.48 and p < 0.05.

关键词： robustness intelligent tutoring systems medical problem-based learning UMLS knowledge acquisition bottleneck.

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Modeling and forecasting of hourly transactions on a WWW and proxy cache server

Modeling and forecasting of hourly transactions on a WWW and...

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1999 Internet Workshop, IWS 1999

作者： Tantatsanawong, Panjai Phien, Huynh Ngoc Kanchanasut, Kanchana Computer Science and Information Management Program School of Advanced Technologies Asian Institute of Technology Thailand

ISBN: (纸本)0780359259

A modeling approach is introduced in this paper to capture the real characteristics of the WWW traffic, using a combination of Box-Jenkins models with seasonality removal. Fourier analysis and standardization are used to render seasonal data into non-seasonal data. However, seasonality cannot be completely removed by this approach, so both seasonal and non-seasonal models are employed and the best models are selected using posterior possibility criterion (PPC). In order to improve the forecasting accuracy, forecast values obtained by the developed models are adjusted by the difference percentage of the day of the week and by using this percentage adjusted values in place of the actual data, which are not available at the time of forecasting. With this adjustment, the developed models can provide very accurate forecast values, except for the case where the higher level of hierarchical proxy is shared by child proxies located in a different time zone. © 1999 IEEE.

关键词： Forecasting

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A comparative analysis of techniques for predicting academic performance

A comparative analysis of techniques for predicting academic...

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37th Annual Frontiers in EducationConference

作者： Nghe, Nguyen Thai Janecek, Paul Haddawy, Peter Computer Science and Information Management Program Asian Institute of Technology (AIT) 12120 Thailand AIT Thailand Can Tho University Viet Nam

ISBN: (纸本)9781424410835

This paper compares the accuracy of Decision Tree and Bayesian Network algorithms for predicting the academic performance of undergraduate and postgraduate students at two very different academic institutes: Can Tho University (CTU), a large national university in Viet Nam;and the Asian Institute of Technology (AIT), a small international postgraduate institute in Thailand that draws students from 86 different countries. Although the diversity of these two student populations is very different, the data-mining tools were able to achieve similar levels of accuracy for predicting student performance: 73/71% for {fail, fair, good, very good} and 94/93% for {fail, pass} at the CTU/AIT respectively. These predictions are most useful for identifying and assisting failing students at CTU (64% accurate), and for selecting Very Good students for scholarships at the AIT (82% accurate). In this analysis, the Decision Tree was consistently 3-12% more accurate than the Bayesian Network. The results of these case studies give insight into techniques for accurately predicting student performance, compare the accuracy of data mining algorithms, and demonstrate the maturity of open source tools.

关键词： Bayesian Networks data mining Decision Trees prediction

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A collaborative intelligent tutoring system for medical problem-based learning

A collaborative intelligent tutoring system for medical prob...

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IUI 04: 2004 International Conference on Intelligent User Interfaces

作者： Suebnukarn, Siriwan Haddawy, Peter Computer Science and Information Management Program Asian Institute of Technology PO Box 4 Pathumthani Thailand

This paper describes COMET, a collaborative intelligent tutoring system for medical problem-based learning. The system uses Bayesian networks to model individual student knowledge and activity, as well as that of the group. It incorporates a multi-modal interface that integrates text and graphics so as to provide a rich communication channel between the students and the system, as well as among students in the group. Students can sketch directly on medical images, search for medical concepts, and sketch hypotheses on a shared workspace. The prototype system incorporates substantial domain knowledge in the area of head injury diagnosis. A major challenge in building COMET has been to develop algorithms for generating tutoring hints. Tutoring in PBL is particularly challenging since the tutor should provide as little guidance as possible while at the same time not allowing the students to get lost. From studies of PBL sessions at a local medical school, we have identified and implemented eight commonly used hinting strategies. We compared the tutoring hints generated by COMET with those of experienced human tutors. Our results show that COMET's hints agree with the hints of the majority of the human tutors with a high degree of statistical agreement (McNemar test, p = 0.652, Kappa = 0.773). Copyright 2004 ACM.

关键词： Learning systems

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A bibliometric analysis on e-government and tourism 6

A bibliometric analysis on e-government and tourism

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6th International Conference on information management and Technology, ICIMTech 2021

作者： Nindito, Hendro Prabowo, Harjanto Leslie Hendric, Spits Warnars Harco Sfenrianto Bina Nusantara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

E-Government and Tourism are fields of research that are constantly evolving. Where tourism services are one of the major foreign exchange earners for most countries. Governments in various countries are trying their best in providing services by utilizing information technology. The purpose of this research is to find out and map the scientific publications that have been carried out on the topics of e-government and tourism indexed by Scopus scientific publications, published from 2000 to 2020. So that research trends in this field can be seen and provide insights for further research. This research uses the bibliometric analysis method. Results showed that the most cited research topic was the recommendation system topic with 639 citations, the country that contributed the most documents was China and the most affiliated contributors were Georgia College State universities and Sydney University of Technology with each producing four articles. This study also contributes to knowledge by proposing classification characteristics of egovernment and tourism with the theme: Websites, Applications, Services, and Electronics. This characteristic abbreviated as WASE. © 2021 IEEE.

关键词： e-government

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Neural controller design for a class of nonlinear systems with time-varying delay: A bibliometric analysis-based short literature review

Neural controller design for a class of nonlinear systems wi...

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2023 International Conference on computer science, information Technology and Engineering, ICCoSITE 2023

作者： Wijaya, Santo Gaol, Ford Lumban Wibowo, Antoni Zarlis, Muhammad Bina Nusantara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Information System Management Information System Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350320954

Real-world practical systems inherently exhibit non-linearities in their dynamics. Also, it is known that a time-varying delay exists in the system state or input-output. Combined, it affects the stability of the closed-loop system. It also increases the complexity of the controller design. In-depth controller design research on the class of Nonlinear Systems with Time-Varying Delay (NSTVD) has been the focus of the control community for many years. However, there is a lack of Systematic Literature Review (SLR) and classifications of the papers on this topic. This paper aims to review controller design utilizing a neural network model for the class of NSTVD systems. The study employs Kitchenham's SLR method to gather, analyze and synthesize published papers from reliable databases between 2017 and 2021. The bibliometric analysis for the selected 38 papers reveals the prolific authors, countries, affiliations, publishers, co-authorship network, co-occurrences of keywords, and ten most-cited papers. Finally, this paper developed a conceptual map outlining six multi-layered findings: the addressed problem, control design method, nonlinear system properties, time-varying delay properties, system constraint properties, and actuator limit properties. A brief qualitative analysis of the ten most-cited papers is performed based on the map. The findings highlighted that the proposed methods have shown encouraging results in the simulation domain and can be used as a source of inspiration for future studies and implementation of the neural controller design of the NSTVD system. © 2023 IEEE.

关键词： Nonlinear systems

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Evaluation of the used of visual electronic banking system application using UTAUT 2 in Bank Central Asia corporation 2

Evaluation of the used of visual electronic banking system a...

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2nd Nommensen International Conference on Technology and Engineering, NICTE 2018

作者： Fajar, Ahmad Nurul Johanes, Frits Septian Girsang, Abba Suganda Wang, Gunawan Information Systems Management Department BINUS Graduate Program-Master of Information System Management Bina Nusantara University Jakarta Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information System Management Bina Nusantara University Jakarta Indonesia Infor. Systems Management Department BINUS Graduate Program-Master of Information System Management Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

The purpose of this study is to determine the factors that encourage the use of visual electronic banking system (VEBS) application in Bank Central Asia Corporation, and provide an idea to increase the use of VEBS. This study using UTAUT 2 model approach. The primary data obtained from interviews, direct observation and questionnaires that distributed and processed using SEM-PLS. The results of this study provide qualitative calculation results of UTAUT 2 variable. The conclusion obtained that interest of the use of application VEBS affected by variables facilitating condition, performance expectancy and behavioral intention. From these conclusions this study provided an idea to the future development of application's features for more effective and efficient use. © Published under licence by IOP Publishing Ltd.

关键词： Surveys

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Recent Trends for Text Summarization in Scientific Documents 9

Recent Trends for Text Summarization in Scientific Documents

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9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Sukmandhani, Arief Agus Arifin, Yulyani Zarlis, Muhammad Budiharto, Widodo Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350370126

Text summarization is a natural language processing (NLP) technique in artificial intelligence that has been studied in recent years. Every document containing text is tested to get a good summary result. In producing a good summary, proper accuracy is required;therefore, various techniques and methods are used, and another challenge is the use of language in the documents being tested. Various types of documents have been used as research for text summarization, including scientific documents, so researchers are interested in studying them more intensely to get the state of the art in research. This research was conducted to review previous research using literature studies from various publications that published research on text summarization in scientific documents. The researcher collected data from several publishers who had published this type of research from 1988 to 2023 quarter 1 and obtained three hundred and eleven articles, then the researcher analyzed the data using the Kitchenham method to get the right literature to answer the research question. Thirty-seven articles were selected for further in-depth analysis. In addition, the researcher found some interesting findings beyond the research question, including other techniques used to solve the text summarization problem and other types of output that are not commonly produced so that it can increase knowledge in researching text summarization. © 2023 IEEE.

关键词： Text processing

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