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Internet of Medical Things: A Bibliometric Analysis of Research Publications from 2018–2022 4th

Internet of Medical Things: A Bibliometric Analysis of Resea...

引用

4th International Conference on Electronics, Biomedical Engineering, and Health informatics, ICEBEHI 2023

作者： Maulana, Fairuz Iqbal Lestari, Dian Adi, Puput Dani Prasetyo Arifin, Mohammad Nazir Purnomo, Agung Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819714629

The field of the Internet of Medical Things (IoMT) is experiencing significant growth as it involves the integration of medical devices and systems with the internet and various digital technologies. This study provides a bibliometric analysis of scholarly articles pertaining to the Internet of Medical Things (IoMT) during the time frame of 2018 to 2022. The analysis is conducted using data sourced from the Scopus database. A total of 1165 documents were identified and analyzed to gain insights into the current state of research in this field. The analysis includes trends in publication output, top authors and institutions, and key research topics. The results of the analysis indicate a steady increase in publication output on IoMT over the past five years, with the highest number of publications in 2022. The top authors in this field were Mohanty, S.P., Kougianos, E., and Pirbhulal, S., while the top institutions were King Saud University, Chinese Academy of Sciences, and University of North Texas. Co-citation analysis revealed that wearable devices, telemedicine, and data analytics were among the key research topics in IoMT. This bibliometric analysis offers useful insights into the present research landscape of the Internet of Medical Things (IoMT) spanning the years 2018 to 2022. The findings can be beneficial for researchers, practitioners, policymakers, and funding agencies in understanding the trends and priorities in this field. The top authors and institutions identified in this analysis can serve as valuable resources for collaboration and staying updated on the latest developments in IoMT. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital devices

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Implications of the Usage of Three-Mode Principal Component Analysis with a Fixed Polynomial Basis 15th

Implications of the Usage of Three-Mode Principal Compone...

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15th International KES Conference on Intelligent Decision Technologies, KESIDT 2023

作者： Monden, Rei Nagai, Isamu Yanagihara, Hirokazu Informatics and Data Science Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Higashi-Hiroshima739-8521 Japan Faculty of Liberal Arts and Science Chukyo University Aichi Nagoya466-8666 Japan Mathematics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Higashi-Hiroshima739-8526 Japan

ISBN: (纸本)9789819929689

When I subjects answer questions regarding J variables K times, the data can be stored in a three-mode data set of size I× J× K. Among the various component analysis approaches to summarize such data, Three-mode Principal Component Analysis (3MPCA) is often used. 3MPCA expresses a three-mode data set by means of A-, B-, and C-mode components and a core array, but this approach is not suitable for predicting data at unobserved time points. To handle this issue, the current study suggests a fixed orthonormal polynomial basis for the 3MPCA model. Briefly, we fix the C-mode component matrix with an orthonormal polynomial basis. More specifically, i) measurement time points, and ii) log transformation of the measurement time points were used as an orthonormal polynomial basis. The use of our proposed methods was demonstrated by applying them to a longitudinal data set collected from patients with depression. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Principal component analysis

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Estimation Algorithms for MLE of Three-Mode GMANOVA Model with Kronecker Product Covariance Matrix 15th

Estimation Algorithms for MLE of Three-Mode GMANOVA Model ...

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15th International KES Conference on Intelligent Decision Technologies, KESIDT 2023

作者： Horikawa, Keito Nagai, Isamu Monden, Rei Yanagihara, Hirokazu Informatics and Data Science Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Higashi-Hiroshima739-8521 Japan Faculty of Liberal Arts and Science Chukyo University Aichi Nagoya466-8666 Japan Mathematics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Higashi-Hiroshima739-8526 Japan

ISBN: (纸本)9789819929689

Currently, there are a lot of measurement data on different items collected over time. The GMANOVA model is appropriate for analyzing the trends in such data, in order to analyze some longitudinal data collected on different items simultaneously, we need to create separate GMANOVA models, but separate GMANOVA models cannot reveal the relationships between items. Also, if we try to apply one model to all of these data, the problem arises that there are too many parameters and the covariance structure is too large. Therefore, we propose an extended GMANOVA model and two estimation algorithms. The proposed model’s covariance matrix has a Kronecker structure. Therefore, because the estimator cannot be uniquely determined using the log-likelihood, we propose two parameter estimation algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Covariance matrix

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Analysis of the Echo Chamber Caused by Unexpected Opinions

Analysis of the Echo Chamber Caused by Unexpected Opinions

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International Conference on Information and Computer Technologies (ICICT)

作者： Akira Nakagawa Yuichi Sei Yasuyuki Tahara Akihiko Ohsuga Management Science and Social Informatics Program The University of Electro-Communications Tokyo Japan Department of Infomatics The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350385625

ISBN: (纸本)9798350385632

Recently, with the widespread use of social media, the speed of information dissemination has significantly increased. As a result, users have started selectively consuming information, leading to a bias in information consumption. One prominent phenomenon of information consumption bias is the echo chamber effect. While the social impact of the echo chamber effect is diverse, notable instances include its influence on health and politics. These cases highlight situations not adequately captured by the conventional definition of the echo chamber effect. In response, this study proposes a new definition of echo chambers, aiming to explore instances where opinions are not only reinforced but also undergo *** substantiate this proposal, the study employs specific verification methods. It investigates differences in the distribution of singularity at points of opinion reinforcement and change. Additionally, it explores variances in the emotional impact of video content and the distribution of echo chamber scores. The findings demonstrate that echo chambers occur not only when opinions are reinforced but also when they undergo changes. The newly proposed definition of the echo chambers suggests a situation where individuals immerse themselves in opinions that pique their interest, regardless of their own thoughts, resulting in a feedback loop of reinforcing and potentially changing perspectives.

关键词： Feedback loop Social networking (online) Vaccines Proposals

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Supervised Learning Models for Early Detection of Albuminuria Risk in Type-2 Diabetes Mellitus Patients 10

Supervised Learning Models for Early Detection of Albuminuri...

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10th International Conference on Advanced informatics: Concept, Theory and Application, ICAICTA 2023

作者： Muharram, Arief Purnama Tahapary, Dicky Levenus Lestari, Yeni Dwi Sarayar, Randy Dirjayanto, Valerie Josephine School of Electrical Engineering and Informatics Master Program of Informatics Institut Teknologi Bandung Bandung Indonesia Indonesia Medical Education and Research Institute Universitas Indonesia Metabolic Disorder Cardiovascular and Aging Research Center Faculty of Medicine Jakarta Indonesia Universitas Indonesia Faculty of Medicine Cipto Mangunkusumo General Hospital Ophthalmology Department Jakarta Indonesia Universitas Indonesia Faculty of Medicine Jakarta Indonesia

ISBN: (纸本)9798350329919

Diabetes, especially T2DM, continues to be a significant health problem. One of the major concerns associated with diabetes is the development of its complications. Diabetic nephropathy, one of the chronic complication of diabetes, adversely affects the kidneys, leading to kidney damage. Diagnosing diabetic nephropathy involves considering various criteria, one of which is the presence of a pathologically significant quantity of albumin in urine, known as albuminuria. Thus, early prediction of albuminuria in diabetic patients holds the potential for timely preventive measures. This study aimed to develop a supervised learning model to predict the risk of developing albuminuria in T2DM patients. The selected supervised learning algorithms included Naive Bayes, Support Vector Machine (SVM), decision tree, random forest, AdaBoost, XGBoost, and Multi-Layer Perceptron (MLP). Our private dataset, comprising 184 entries of diabetes complications risk factors, was used to train the algorithms. It consisted of 10 attributes as features and 1 attribute as the target (albuminuria). Upon conducting the experiments, the MLP demonstrated superior performance compared to the other algorithms. It achieved accuracy and f1-score values as high as 0.74 and 0.75, respectively, making it suitable for screening purposes in predicting albuminuria in T2DM. Nonetheless, further studies are warranted to enhance the model's performance. © 2023 IEEE.

关键词： Forecasting

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GPT Attack for Adversarial Privacy Policies

GPT Attack for Adversarial Privacy Policies

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International Conference on Big Data Computing and Communications (BIGCOM)

作者： Isaac Joy Jun Wu Jingrui He Informatics Program UIUC Champaign USA Department of Computer Science UIUC Champaign USA School of Information Sciences UIUC Champaign USA

ISBN: (数字)9798331509538

ISBN: (纸本)9798331509545

While Machine Learning (ML) is widely used in many industries, one sector that is just beginning to leverage this technology is the legal field. Efforts like the construction of the OPP-115 Privacy Policy corpus make it possible to train Natural Language Processing (NLP) and ML models for legal use, and tools such as Polisis, Claudette, etc., which utilize these models can now provide users with descriptive annotations of various types of contracts, including Privacy Policies. However, these tools remain vulnerable to adversarial attacks, specifically adversarial legal documents, which differ from typical text based adversarial attacks due to the necessity of preserving the continuity of a legal document. Therefore, focusing on the OPP-115 corpus and Polisis specifically, we propose a framework that consists of a Doc2Vec model and a variety of shallow and deep learning methods for classification, followed by adversarial attacks on Privacy Policy segments which utilize GPT 3.5, a state-of-the-art LLM, in order to create an adversarial Privacy Policy. We evaluate the effectiveness of our method by comparing attack results to those produced by current methods, including Bert Attack and Text Fooler. Our procedure reveals not just that an attack using GPT 3.5 is an effective means of producing an adversarial policy, but that it is surprisingly easy to prompt a widely used state-of-the-art LLM to perform such a task.

关键词： Deep learning Industries Privacy Law Annotations Focusing Benchmark testing Big Data Natural language processing Contracts

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Unveiling Factors Affecting Intentions to Use ChatGPT: Perspectives from Indonesian Higher Education Students

Unveiling Factors Affecting Intentions to Use ChatGPT: Persp...

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International Conference on informatics and Computing (ICIC)

作者： Zaenal Abidin Kongkiti Phusavat Riza Arifudin Endang Sugiharti Study Program of Informatics Engineering Universitas Negeri Semarang Semarang Indonesia Industrial Enginering Faculty of Engineering Kasetsart University Bangkok Thailand

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

ChatGPT has generated significant interest and discussion within the academic community since its initial introduction. This study aims to investigate the students’ intentions to use ChatGPT for educational purposes in higher education. A proposed conceptual model based on the unified theory of acceptance and use of technology model-2 (UTAUT2) was employed in this current study. A total of 575 data obtained from a questionnaire survey of higher education students were analyzed using partial least square-structural equation modeling (PLS-SEM). The results of the hypothesis testing revealed that both cognitive attitude and emotional attitude have a significant influence on the intention to use ChatGPT. The cognitive attitude was influenced by performance expectancy and effort expectancy. Affective attitudes were shaped by factors such as novelty value, performance expectancy, hedonic motivation, and effort expectancy.

关键词： Surveys Analytical models Education Position measurement Chatbots Mathematical models Data models informatics Testing

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How Is the Quality of Information in a Cancer Hospital Regarding the Completeness and Consistency? A Case Study of the Hospital Cancer Registry of the Brazilian Hospital Bom Pastor 18

How Is the Quality of Information in a Cancer Hospital Regar...

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18th World Congress on Medical and Health informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021

作者： Assis, Erika G. Lima, Anna Carolina L. Nobre, Cristiane Neri Graduate Program in Informatics Pontifical Catholic University of Minas Gerais Minas Gerais Belo Horizonte Brazil Promove Faculty of Technology Minas Gerais Belo Horizonte Brazil

ISBN: (纸本)9781643682648

This study aimed to analyze the measurement of information quality in the Information System of the Brazilian Hospital in terms of data completeness and consistency. The quality of information is a fundamental factor in evaluating the performance of information systems. Its use is a reasonable condition in the management of the health service and attention to the care of patients. The research had a retrospective, descriptive character exploratory with quantitative analysis of the data. The study had some limitations, we observed incomplete information regarding some studied variables;this is because the primary source of information in the cancer registry is the patient's medical record. Therefore, the patient's medical records are relevant and should contain the entire health history, from birth to death. In addition, they support research, the management of health services. © 2022 International Medical informatics Association (IMIA) and IOS Press.

关键词： Hospitals

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Beyond the Scroll: Eye-Tracking Evaluations on the National Gallery of Indonesia’s Instagram 26th

Beyond the Scroll: Eye-Tracking Evaluations on the National ...

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26th International Conference on Asia-Pacific Digital Libraries, ICADL 2024

作者： Sari, Desy Novita Prameswari, Clarissa Rahmi Anshori, Isa Master’s Program in Library Science Universitas Indonesia Kota Depok Indonesia Department of Library and Information Sciences Universitas Indonesia Kota Depok Indonesia Biomedical Engineering Department School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia National Gallery of Indonesia Central Jakarta Indonesia

ISBN: (纸本)9789819608676

Eye-tracking studies focused on art galleries and museums within the realm of Instagram, especially in the Indonesian context, are notably scant. This investigation elucidates the user interaction and experience of the art gallery’s Instagram account, @galerinasional. Employing a quantitative approach, we implemented eye-tracking experiments using the well-known online eye-tracking software RealEye. The study participants were followers of the National Gallery of Indonesia’s (Galnas) Instagram profile, seven women and three men, in two age brackets: 18–24 years (n = 5) and 25–34 years (n = 5). The experimental protocol required participants to execute five tasks centered on locating exhibition details and artwork on the Galnas Instagram platform, with a duration of 100 s allocated to each task. The Participant Quality Grade (PQG), examination duration, optimal browser dimensionality, K-factor mean, gaze and fixation frequencies, and heat maps were determined for the participants. The key findings are as follows. (1) The participants’ PQG scores were predominantly between 4 and 6. (2) Investigative browsing typically exceeded the 100-s limit. (3) The consensus on the ideal browser dimensions hovered around 1,368.6 × 814.8 px. (4) The K-factor mean across participants tended toward K > 0. (5) The average gaze occurrence was 27 items per second for most participants. (6) A noticeable disparity in fixation counts was observed between the two age groups, with individuals aged 25–34 demonstrating prolonged engagement with Galnas’ content. (7) Heat maps accentuated a pronounced concentration on visual content, encompassing photographs, videos, and their associated captions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Economic and social effects

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Computational thinking through an online game to develop soft and hard skills

Computational thinking through an online game to develop sof...

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EAEEIE Annual Conference,

作者： Adriano Fiad Farias Dante Augusto Couto Barone Graduate Program in Informatics in Education Federal University of Rio Grande do Sul Porto Alegre Brazil

Currently we see globalization and technological advances accelerating worldwide, transforming the world of work and human coexistence. We still notice that the educational systems, in their majority, are disconnected from these global realities. In this sense, it is necessary to have an educational formation more aligned to the contemporary world, preparing young people for the challenges of the 21st century, how to deal with technological resources and processes, developing soft and hard skills. In this way, it can be observed that in recent years computational thinking has gained relevance in this scenario, being a field of research in the most varied areas of knowledge, developing communication skills, creativity, leadership, problem solving, familiarity with technologies, management, transforming young people into autonomous individuals who are prepared for the technological changes that the world requires. Taking these transformations as a reference, this paper describes/presents the development of an online tool to stimulate computational thinking in elementary school, through online games. he use of the ThinkinGame makes it possible to identify the pillars to be worked on with young people, after its use, thus improving the approaches to be given in the formation of these young people, being able to turn attention to the challenge of teaching additional skills, such as sophisticated thinking and flexible problem solving.

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