Information Systems Frontiers最新文献_第3页

Factors Affecting Big Data Analytics Adoption in Small and Medium Enterprises 影响中小企业采用大数据分析的因素

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-30 DOI: 10.1007/s10796-024-10538-2

Rawan Babalghaith, Amer Aljarallah

引用次数: 0

Augmented Reality to Assist in the Diagnosis of Temporomandibular Joint Alterations 辅助诊断颞下颌关节病变的增强现实技术

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-27 DOI: 10.1007/s10796-024-10545-3

Laura Cercenelli, Nicolas Emiliani, Chiara Gulotta, Mirko Bevini, Giovanni Badiali, Emanuela Marcelli

{"title":"Augmented Reality to Assist in the Diagnosis of Temporomandibular Joint Alterations","authors":"Laura Cercenelli, Nicolas Emiliani, Chiara Gulotta, Mirko Bevini, Giovanni Badiali, Emanuela Marcelli","doi":"10.1007/s10796-024-10545-3","DOIUrl":"https://doi.org/10.1007/s10796-024-10545-3","url":null,"abstract":"Augmented Reality (AR) is an increasingly prominent technology with diverse applications across various surgical disciplines. This study aims to develop and assess the feasibility of a novel AR application intended to aid surgeons in the clinical assessment of temporomandibular joint (TMJ) alterations necessitating surgical intervention. The application employs a multi-modality tracking approach, combining both marker-less and marker-based tracking techniques to concurrently track the fixed portion of the joint and the movable mandible involved in TMJ. For the marker-based tracking both a planar marker with a binary QR-code pattern and a cuboid marker that contains a unique QR-code pattern on each face were tested and compared. The AR application was implemented for the HoloLens 2 head-mounted display and validated on a healthy volunteer performing the TMJ task, i.e. the opening and closing of the mouth. During the task, video recordings from the HoloLens cameras captured the horizontal and vertical excursions of the jaw movements (TMJ movements) using virtual markers anchored to the AR-displayed virtual anatomies. For validation, the video-recorded TMJ movements during AR viewing were compared with standard kinesiographic acquisitions. The findings demonstrated the consistency between the AR-derived trajectories and the kinesiography curves, especially when using the cubic Multi Target tracker to follow the moving mandible. Finally, the AR application was experienced on a patient and it was extremely useful for the surgeon to diagnose alterations in the normal kinematics of the TMJ. Future efforts should be addressed to minimize the bulkiness of the tracker and provide additional visual cues for surgeons.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"25 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding the Drivers of Industry 4.0 Technologies to Enhance Supply Chain Sustainability: Insights from the Agri-Food Industry 了解工业 4.0 技术对提高供应链可持续性的推动力：农业食品行业的启示

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-26 DOI: 10.1007/s10796-024-10539-1

Guoqing Zhao, Xiaoning Chen, Paul Jones, Shaofeng Liu, Carmen Lopez, Leonardo Leoni, Denis Dennehy

{"title":"Understanding the Drivers of Industry 4.0 Technologies to Enhance Supply Chain Sustainability: Insights from the Agri-Food Industry","authors":"Guoqing Zhao, Xiaoning Chen, Paul Jones, Shaofeng Liu, Carmen Lopez, Leonardo Leoni, Denis Dennehy","doi":"10.1007/s10796-024-10539-1","DOIUrl":"https://doi.org/10.1007/s10796-024-10539-1","url":null,"abstract":"The sustainability of agri-food supply chains (AFSCs) is severely threatened by regional and global events (e.g., conflicts, natural and human-made disasters, climate crises). In response, the AFSC industry is seeking digital solutions using Industry 4.0 (I4.0) technologies to enhance resilience and efficiency. However, why I4.0 adoption remains stubbornly low in the agri-food industry remains poorly understood. To address this gap, this study draws on middle-range theory (MRT) and uses thematic analysis, the fuzzy analytic hierarchy process, total interpretive structural modelling, and fuzzy cross-impact matrix multiplication applied to classification to produce insights from nine case studies in China that have invested in I4.0 technologies to improve their AFSC sustainability. New drivers of I4.0 unique to the agri-food industry are identified, showing how I4.0 can contribute to the environmental, economic, and social dimensions of AFSC sustainability. The results have implications for AFSC researchers and practitioners with an interest in supply chain sustainability.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"6 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Combating Online Malicious Behavior: Integrating Machine Learning and Deep Learning Methods for Harmful News and Toxic Comments 打击网络恶意行为：整合机器学习和深度学习方法，应对有害新闻和有毒评论

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-24 DOI: 10.1007/s10796-024-10540-8

Szu-Yin Lin, Shih-Yi Chien, Yi-Zhen Chen, Yu-Hang Chien

{"title":"Combating Online Malicious Behavior: Integrating Machine Learning and Deep Learning Methods for Harmful News and Toxic Comments","authors":"Szu-Yin Lin, Shih-Yi Chien, Yi-Zhen Chen, Yu-Hang Chien","doi":"10.1007/s10796-024-10540-8","DOIUrl":"https://doi.org/10.1007/s10796-024-10540-8","url":null,"abstract":"The surge in online media has inundated the public with information, prompting the use of sensational and provocative language to capture attention, worsening the prevalence of online malicious behavior. This study delves into machine learning (ML) and deep learning (DL) techniques to identify and recognize harmful news and toxic comments, aiming to counteract the detrimental impact on public perception. Effective methods for detecting and categorizing malicious content are proposed and discussed, highlighting the differences between ML and DL approaches in combating malicious behavior. The study employs feature selection methods to scrutinize the distinctive feature set and keywords linked to harmful news and toxic comments. The proposed approach yields promising outcomes, achieving a 94% accuracy rate in recognizing toxic comments, a 68% recognition accuracy for harmful news, and an 81% accuracy in classifying malicious behavior content (combining harmful news and toxic comments). By harnessing the capabilities of ML and DL, this research enriches our comprehension of and ability to mitigate malicious behavior in online media. It provides valuable insights into the practical identification and categorization of harmful news and toxic comments, highlighting the unique facets of these advanced computational strategies as they address the pressing challenges of our digital society.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"17 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142313762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mobile Technology Addiction Effect on Risky Behaviours: the Moderating Role of Use-Regulation 移动技术成瘾对危险行为的影响：使用调节的调节作用

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-17 DOI: 10.1007/s10796-024-10537-3

Makafui Nyamadi, Ofir Turel

引用次数: 0

Towards Sustainability of AI – Identifying Design Patterns for Sustainable Machine Learning Development 实现人工智能的可持续性--确定可持续机器学习开发的设计模式

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-16 DOI: 10.1007/s10796-024-10526-6

Daniel Leuthe, Tim Meyer-Hollatz, Tobias Plank, Anja Senkmüller

{"title":"Towards Sustainability of AI – Identifying Design Patterns for Sustainable Machine Learning Development","authors":"Daniel Leuthe, Tim Meyer-Hollatz, Tobias Plank, Anja Senkmüller","doi":"10.1007/s10796-024-10526-6","DOIUrl":"https://doi.org/10.1007/s10796-024-10526-6","url":null,"abstract":"As artificial intelligence (AI) and machine learning (ML) advance, concerns about their sustainability impact grow. The emerging field \"Sustainability of AI\" addresses this issue, with papers exploring distinct aspects of ML’s sustainability. However, it lacks a comprehensive approach that considers all ML development phases, treats sustainability holistically, and incorporates practitioner feedback. In response, we developed the sustainable ML design pattern matrix (SML-DPM) consisting of 35 design patterns grounded in justificatory knowledge from research, refined with naturalistic insights from expert interviews and validated in three real-world case studies using a web-based instantiation. The design patterns are structured along a four-phased ML development process, the sustainability dimensions of environmental, social, and governance (ESG), and allocated to five ML stakeholder groups. It represents the first artifact to enhance each ML development phase along each ESG dimension. The SML-DPM fuels advancement by aggregating distinct research, laying the groundwork for future investigations, and providing a roadmap for sustainable ML development.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"11 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Innovative Diagnostic Approaches for Predicting Knee Cartilage Degeneration in Osteoarthritis Patients: A Radiomics-Based Study 预测骨关节炎患者膝关节软骨退化的创新诊断方法：基于放射组学的研究

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-12 DOI: 10.1007/s10796-024-10527-5

Francesca Angelone, Federica Kiyomi Ciliberti, Giovanni Paolo Tobia, Halldór Jónsson, Alfonso Maria Ponsiglione, Magnus Kjartan Gislason, Francesco Tortorella, Francesco Amato, Paolo Gargiulo

{"title":"Innovative Diagnostic Approaches for Predicting Knee Cartilage Degeneration in Osteoarthritis Patients: A Radiomics-Based Study","authors":"Francesca Angelone, Federica Kiyomi Ciliberti, Giovanni Paolo Tobia, Halldór Jónsson, Alfonso Maria Ponsiglione, Magnus Kjartan Gislason, Francesco Tortorella, Francesco Amato, Paolo Gargiulo","doi":"10.1007/s10796-024-10527-5","DOIUrl":"https://doi.org/10.1007/s10796-024-10527-5","url":null,"abstract":"Osteoarthritis (OA) is a common joint disease affecting people worldwide, notably impacting quality of life due to joint pain and functional limitations. This study explores the potential of radiomics — quantitative image analysis combined with machine learning — to enhance knee OA diagnosis. Using a multimodal dataset of MRI and CT scans from 138 knees, radiomic features were extracted from cartilage segments. Machine learning algorithms were employed to classify degenerated and healthy knees based on radiomic features. Feature selection, guided by correlation and importance analyses, revealed texture and shape-related features as key predictors. Robustness analysis, assessing feature stability across segmentation variations, further refined feature selection. Results demonstrate high accuracy in knee OA classification using radiomics, showcasing its potential for early disease detection and personalized treatment approaches. This work contributes to advancing OA assessment and is part of the European SINPAIN project aimed at developing new OA therapies.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"52 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-Review 医疗保健领域数字双胞胎的概念框架：来自系统性元综述的证据

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-12 DOI: 10.1007/s10796-024-10536-4

Giulia Pellegrino, Massimiliano Gervasi, Mario Angelelli, Angelo Corallo

引用次数: 0

Adoption of Blockchain E-Voting Service: Digital Literacy as a Mediating Mechanism 区块链电子投票服务的采用：作为中介机制的数字素养

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-07 DOI: 10.1007/s10796-024-10532-8

Mousa Albashrawi, Amir Zaib Abbasi, Lin Li, Umair Rehman

{"title":"Adoption of Blockchain E-Voting Service: Digital Literacy as a Mediating Mechanism","authors":"Mousa Albashrawi, Amir Zaib Abbasi, Lin Li, Umair Rehman","doi":"10.1007/s10796-024-10532-8","DOIUrl":"https://doi.org/10.1007/s10796-024-10532-8","url":null,"abstract":"Blockchain has become a promising technology with huge benefits; nevertheless, its adoption intention has been scarce across different organizations, especially in government-to-citizens service (e.g., blockchain-based e-voting). Therefore, we aim to investigate how blockchain can affect citizens' adoption intention to use blockchain-based e-voting service. We study blockchain adoption intention by employing UTAUT2 as a theoretical base and the Replacement-Amplification-Transformation (R.A.T) technology integration model to study digital literacy as a mediating mechanism in our study model due to its significance in the contemporary business world. On the method side, we obtained 315 valid responses that we utilized to conduct a PLS-SEM-based analysis. Our findings state that digital literacy positively mediates the relationship between five determinants of UTAUT2 (e.g., facilitating conditions, social influence, hedonic motivation, habit, and price value) and citizens' intention to adopt blockchain e-voting service for casting their votes in elections. This study is among the first to examine the mediating mechanism of digital literacy between UTAUT2 factors and citizens' intention to adopt blockchain e-voting service. It is also worthwhile to quote that our study is a pioneer in extending the UTAUT2 model in the context of blockchain e-voting service. Lastly, we communicate the study's theoretical and practical implications to enrich both knowledge and industry.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"1 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142144332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mining Patient-Generated Content for Medication Relations and Transition Network to Predict the Rankings and Volumes of Different Medications 挖掘患者生成内容中的用药关系和过渡网络，预测不同药物的排名和用量

IF 5.9 3区管理学

Information Systems Frontiers Pub Date : 2024-09-07 DOI: 10.1007/s10796-024-10530-w

Yuanyuan Gao, Anqi Xu, Paul Jen-Hwa Hu

{"title":"Mining Patient-Generated Content for Medication Relations and Transition Network to Predict the Rankings and Volumes of Different Medications","authors":"Yuanyuan Gao, Anqi Xu, Paul Jen-Hwa Hu","doi":"10.1007/s10796-024-10530-w","DOIUrl":"https://doi.org/10.1007/s10796-024-10530-w","url":null,"abstract":"Accurate estimates of medication rankings and volumes can benefit patients, physicians, online health communities, pharmaceutical companies, and the healthcare industry at large. This study analyzes patient-generated content in online health communities to discover important medication transition and combination patterns for better ranking and volume predictions. The current research takes a data-driven analytics approach to identify medication information from patient posts and classify different types of medication relations. The identified relation patterns then are represented in a medication relation network with an adjusted transition model for ranking and volume estimates. Evaluation results of real-world patient posts show the proposed method is more effective for predicting medication rankings than existing network-based measures. Moreover, a regression-based model, informed by the proposed method’s network-based outcomes, attains promising accuracy in estimating medication volumes, as revealed by the relatively low mean squared errors. Overall, the proposed method is capable of identifying important features for increased predictive power, as manifested by ({text{R}}^{2}) and adjusted ({text{R}}^{2}) values. It has the potential for better medication ranking and volume predictions, and offers insights for decision making by different stakeholders. This method is generalizable and can be applied in important prediction tasks in healthcare and other domains.","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"71 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142144253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0