Review
Computer Science, Interdisciplinary Applications
Alexander Schniedermann
Summary: The question of how citation impact relates to academic quality is a recurring theme in bibliometric research. While experts have used more complex conceptions of research quality for evaluation, detailed analyses of how impact relates to dimensions like methodological rigor are lacking. Increasing formal guidelines for biomedical research not only provide insight into the social dynamics of standardization, but also their relationships to scientific rewards.
Article
Computer Science, Artificial Intelligence
Bassoma Diallo, Jie Hu, Tianrui Li, Ghufran Ahmad Khan, Ahmed Saad Hussein
Summary: This paper introduces five similarity metric models that address the limitations of traditional Cosine similarity and Euclidean distance metrics. By proposing a more accurate similarity function, the experimental results show that this approach outperforms existing algorithms.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2022)
Article
Computer Science, Artificial Intelligence
Chunrong Wu, Qinglan Peng, Jia Lee, Kenji Leibnitz, Yunni Xia
Summary: Hierarchical clustering method HCNN effectively groups similar data by utilizing structural similarities in the nearest neighbor graph, identifying clusters and outliers while reducing the influence of obscure boundaries. The method merges clusters more efficiently by considering equivalence relations based on maximum similarity, leading to improved clustering efficiency and accuracy.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Karpagalingam Thirumoorthy, Karuppaiah Muneeswaran
Summary: In this study, the Hybrid Jaya Optimization algorithm was utilized for text document clustering, and it achieved the highest quality clustering compared to other techniques.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Leonardo Ramos Emmendorfer, Anne Magaly de Paula Canuto
Summary: A novel linkage criterion for Hierarchical agglomerative clustering (HAC) is proposed and evaluated in this paper, named GAL. Empirical analysis shows that the results obtained by the proposed criterion surpass all existing reference methods in terms of performance.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Teng Li, Amin Rezaeipanah, ElSayed M. Tag El Din
Summary: This paper presents a clustering framework based on ensemble approaches, utilizing Agglomerative Hierarchical Clustering (AHC) methods and a novel similarity measurement. The proposed algorithm, Meta-Clustering Ensemble scheme based on Model Selection (MCEMS), outperforms HMM, DSPA, and WHAC algorithms in terms of clustering accuracy.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Esra Gundogan, Mehmet Kaya
Summary: This study proposes an automatic solution to create conference programs, which improves the efficiency of conference planning by using the SBERT method for article similarity calculation, proposing an equal clustering method, and considering both keyword and article content similarities for topic determination.
INFORMATION PROCESSING & MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Xingcheng Ran, Yue Xi, Yonggang Lu, Xiangwen Wang, Zhenyu Lu
Summary: Data clustering is a widely used technique in various fields to divide objects into different clusters based on similarity measures. Hierarchical clustering methods generate consistent partitions of data at different levels, allowing analysis of complex data structures. This article comprehensively reviews various hierarchical clustering methods, including recent developments, and examines the role of similarity measures in the clustering process.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Review
Medicine, General & Internal
Benjamin Speich, Viktoria L. Gloy, Katharina Klatte, Dmitry Gryaznov, Ala Taji Heravi, Nilabh Ghosh, Ioana R. Marian, Hopin Lee, Anita Mansouri, Szimonetta Lohner, Ramon Saccilotto, Edris Nury, An-Wen Chan, Anette Bluemle, Ayodele Odutayo, Sally Hopewell, Matthias Briel
Summary: This systematic review assessed the reliability of information across registries for trials with multiple registrations, revealing inconsistencies in key trial characteristics across different registries. Further harmonization across clinical trial registries may be necessary to increase their usefulness.
Article
Computer Science, Information Systems
Seyed Mojtaba Sadjadi, Hoda Mashayekhi, Hamid Hassanpour
Summary: In this paper, a concept-based semi-supervised framework for document clustering is proposed, which utilizes both labeled and unlabeled data to improve clustering quality. By extracting relevant concepts and adjusting the cluster centroids, this framework improves the hierarchical clustering approach and demonstrates its superiority in experiments.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
D. Uma Priya, P. Santhi Thilagam
Summary: This paper proposes an embedding-based clustering approach using the SchemaEmbed model to group contextually similar JSON documents. The results show that the proposed method significantly improves clustering quality and demonstrates that clustering results obtained by contextual similarity are superior to those obtained by traditional semantic similarity models.
JOURNAL OF INFORMATION SCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Jenish Dhanani, Rupa Mehta, Dipti Rana
Summary: This study proposes a novel Legal Document Recommendation System based on graph clustering, which efficiently handles a large number of judgments and finds semantically relevant judgments. By restricting the scope of pairwise similarity calculations, the system significantly reduces the computational complexity and improves the efficiency of the recommender system.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Houji Zhou, Yi Li, Xiangshui Miao
Summary: This article introduces a method to accelerate document clustering using memristive in-memory computing, which reduces the time complexity by performing similarity measurement in one step. It also proposes a normalization scheme to reduce normalization steps during clustering and discusses the impact of non-ideal factors in memristors on clustering tasks.
SCIENCE CHINA-INFORMATION SCIENCES
(2022)
Review
Clinical Neurology
Michael von Glischinski, Ruth von Brachel, Christian Thiele, Gerrit Hirschfeld
Summary: The study found that clinician-administered scales are more commonly used in clinical trials as criteria for participant inclusion and defining clinical remission, while self-report questionnaires are primarily used in behavioral trials. The trend has accelerated in the last 20 years. Studies with drug or other interventions tend to use higher cut points to include patients compared to studies on behavioral therapies.
JOURNAL OF AFFECTIVE DISORDERS
(2021)
Article
Computer Science, Artificial Intelligence
Zhiqiang Fu, Yao Zhao, Dongxia Chang, Yiming Wang
Summary: Low-rank representation (LRR) is a powerful method for finding the low-dimensional subspace structure in high-dimensional data spaces, but it may lose the geometric structure of the data. Therefore, a new hierarchical weighted low-rank representation (HWLRR) is proposed in this paper to preserve both local and global structure. Experimental results demonstrate the superiority of the proposed method.
PATTERN RECOGNITION
(2021)
Article
Public, Environmental & Occupational Health
Emily A. Hennessy, Rebecca L. Acabchuk, Pieter A. Arnold, Adam G. Dunn, Yong Zhi Foo, Blair T. Johnson, Sonya R. Geange, Neal R. Haddaway, Shinichi Nakagawa, Witness Mapanga, Kerrie Mengersen, Matthew J. Page, Alfredo Sanchez-Tojar, Vivian Welch, Luke A. McGuinness
Summary: It is crucial to robustly synthesize available evidence to inform and improve prevention efforts and policy, yet barriers such as inaccurate terminology and unclear reporting hinder comprehensive evidence synthesis. Practical guidelines and tools are provided to assist prevention scientists in preparing synthesis-ready research, with step-by-step guidance and software suggestions for standardizing data design and public archiving to facilitate synthesis-ready research. Using a recent mindfulness trial as an example, ways to ensure discoverability of primary studies and the presence of necessary data are demonstrated.
PREVENTION SCIENCE
(2022)
Article
Substance Abuse
Samia Amin, Liliana Laranjo, Adam G. Dunn
Summary: The study findings suggest that higher social acceptability of e-cigarettes in workplaces or educational settings is associated with increased likelihood of use or intention to use among individuals.
JOURNAL OF ADDICTIVE DISEASES
(2022)
Article
Medicine, Research & Experimental
Rabia Bashir, Adam G. Dunn
Summary: This study aims to investigate the characteristics of clinical trials associated with earlier results reporting on ClinicalTrials.gov. The results show that non-industry, non-drug, and earlier phase trials report results on ClinicalTrials.gov more slowly. The findings suggest that incentives and tools targeting these types of trials are also needed to improve trial reporting.
CONTEMPORARY CLINICAL TRIALS
(2022)
Article
Multidisciplinary Sciences
Joyce Siette, Laura Dodds, Didi Surian, Mirela Prgomet, Adam Dunn, Johanna Westbrook
Summary: This study examined the frequency and duration of social interactions among residents in aged care facilities and their association with quality of life. The results showed a positive correlation between time spent with other residents and quality of life, while time spent with facility staff was negatively correlated with quality of life.
Review
Computer Science, Interdisciplinary Applications
Farhana Pethani, Adam G. Dunn
Summary: The objective of this study was to review the applications of natural language processing (NLP) for information extraction and retrieval from clinical notes in dentistry. A search strategy was implemented in EMBASE, CINAHL, and Medline to identify relevant studies. A total of 17 studies were included, demonstrating heterogeneity in study design and reporting quality. The findings suggest a need for standardization in reporting and improved connections between NLP methods and applied NLP in dentistry.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Review
Computer Science, Information Systems
Didi Surian, Ying Wang, Enrico Coiera, Farah Magrabi
Summary: This research summarizes the literature on evaluating automated methods for early detection of safety problems with health information technology (HIT). The study found that various rule-based, statistical, and machine learning methods have been applied to automate the detection of HIT safety problems, but there are still many opportunities to study their application and effectiveness in real-world settings.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
Editorial Material
Biochemistry & Molecular Biology
Isabelle Boisvert, Adam G. Dunn, Erik Lundmark, Jennifer Smith-Merry, Wendy Lipworth, Amber Willink, Sarah E. Hughes, Michele Nealon, Melanie Calvert
Article
Health Care Sciences & Services
Divya Ramjee, Catherine C. Pollack, Marie-Laure Charpignon, Shagun Gupta, Jessica Malaty Rivera, Ghinwa El Hayek, Adam G. Dunn, Angel N. Desai, Maimuna S. Majumder
Summary: During the COVID-19 pandemic, there were fluctuating policies on face mask use by the US Centers for Disease Control and Prevention. Analyzing sentiment on masks surrounding guideline changes can inform future communication strategies and improve widespread and sustained adoption.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Health Care Sciences & Services
Julie Ayre, Carissa Bonner, Danielle M. Muscat, Adam G. Dunn, Eliza Harrison, Jason Dalmazzo, Dana Mouwad, Parisa Aslani, Heather L. Shepherd, Kirsten J. McCaffery
Summary: The SHeLL Health Literacy Editor is an automated tool that provides objective and specific guidance for producing easy-to-read health information. It improves the quality and safety of written health information by offering immediate feedback on various aspects, such as readability and person-centered language. It can be used as a scalable intervention to promote the adoption of health literacy guidelines by health services and information providers.
JMIR FORMATIVE RESEARCH
(2023)
Article
Mathematical & Computational Biology
Shifeng Liu, Florence T. Bourgeois, Claire Narang, Adam G. Dunn
Summary: This study compared different methods for finding relevant trial registrations using a PROSPERO entry, without prior screening. The results showed that term-based representations and MetaMap outperformed PICO extraction in ranking trial registrations. When ranking trial articles, term-based representations were the best performing approach. These findings suggest that automated methods can reduce workload in systematic reviews, but additional processes are still needed to efficiently identify relevant trial registrations or trial articles.
RESEARCH SYNTHESIS METHODS
(2023)
Article
Computer Science, Cybernetics
Usman Naseem, Matloob Khushi, Jinman Kim, Adam G. Dunn
Summary: People on social media using disease and symptom words to discuss their health can introduce biases in data-driven public health applications. This study presents a new dataset called RHMD, which consists of 10,015 manually annotated Reddit posts. The dataset is labeled with four categories and provides a comprehensive performance analysis of baseline methods. The release of this dataset is expected to facilitate the development of new methods for detecting health mentions in user-generated text.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Primary Health Care
Hooi Min Lim, Chirk Jenn Ng, Adam G. Dunn, Adina Abdullah
Summary: This study explores the views and experiences of patients with high cardiovascular risk on online health information-seeking about statins, and how this information influences their decisions. The results suggest that patients need different types of online health information throughout their disease trajectory, and unintentional passive exposure to online health information has an influence on patients' adherence to statins. The quality of patient-doctor communication in relation to online health information-seeking behavior remains critical for patient decision-making.
Article
Computer Science, Information Systems
Zubair Shah, Adam G. Dunn
Summary: This research proposes a new approach to event localization and ranking by modeling the use of language in tweets. It detects unexpected changes in language usage and identifies anomalies across cities, countries, and time periods.
IEEE TRANSACTIONS ON BIG DATA
(2022)
Article
Computer Science, Cybernetics
Usman Naseem, Matloob Khushi, Jinman Kim, Adam G. Dunn
Summary: The article introduces a hybrid text representation method for explaining suicide risk identification on social media. The method achieves excellent results on a public suicide dataset and demonstrates advantages in clinical and public health practice.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2022)
