Dog Bites and Rabies in the Eastern Region of Ghana in 2013–2015: A Call for a One-Health Approach by Boakye-Yiadom Adomako, Frank Baiden, Samuel Sackey, Donne Kofi Ameme, Fred Wurapa, Kofi Mensah Nyarko, Ernest Kenu, Edwin Afari

“…We followed up with interviews with three key informants from the health and veterinary services on issues related to surveillance and data quality. Results. Overall, 4821 dog bites were reported over the three-year period. …”
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Fault diagnosis of a CNC hobbing cutter through machine learning using three axis vibration data by Nagesh Tambake, Bhagyesh Deshmukh, Sujit Pardeshi, Sachin Salunkhe, Robert Cep, Emad Abouel Nasr

“…The proposed framework demonstrated superior performance compared to existing methodologies in the literature, addressing key gaps such as overfitting, data quality, and model explainability. Real-world deployment challenges, including diverse operating conditions and generalizability across machines, were also discussed, with recommendations for incorporating multi-sensor data and transfer learning approaches in future research. …”
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Seroprevalence of TORCH Viral Agents in Pregnant Women in Turkey: Systematic Review and Meta-Analysis by Elmas Pinar Kahraman Kilbas, Ihsan Hakki Ciftci, Imdat Kilbas, Hande Toptan

“…A total of 60 studies meeting the inclusion criteria were included. Data quality control was assessed using the Joanna Briggs Institute guideline prevalence studies checklist. …”
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A comparative approach of analyzing data uncertainty in parameter estimation for a Lumpy Skin Disease model by Edwiga Renald, Miracle Amadi, Heikki Haario, Joram Buza, Jean M. Tchuenche, Verdiana G. Masanja

“…This study has introduced a novel yet simple technique for analyzing data uncertainties in compartmental models which is then used to examine the reliability of a deterministic model of the transmission dynamics of LSD in cattle which involves investigating scenarios related to data quality for which the model parameters can be well identified. …”
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An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets by Adam S. L. Graefe, Miriam R. Hübner, Filip Rehburg, Steffen Sander, Sophie A. I. Klopfenstein, Samer Alkarkoukly, Ana Grönke, Annic Weyersberg, Daniel Danis, Jana Zschüntzsch, Elisabeth F. Nyoungui, Susanna Wiegand, Peter Kühnen, Peter N. Robinson, Oya Beyan, Sylvia Thun

“…Abstract Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. …”
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Does electronic data collection perform better than paper-based data collection in health research fieldwork? A participatory action research in Zanzibar by Ving Fai Chan, Fatma Omar, Eden Mashayo, Ai Chee Yong, Christine Graham, Ronnie Graham, Omar Juma Othman, Jamison Jones, Kajal Shah

“…Introduction Technological advancement in low-resource settings is opening the gateway to implementation of electronic data collection methods that improve data quality. We examined the concerns to use electronic data collection tool in Zanzibar, codeveloped a tool that addressed the concerns and evaluated the process and limitations of incorporating an electronic data collection tool aside from paper-based during a community-based study in Zanzibar.Methods The science of improvement Plan-Do-Study-Act model guided this mixed-method participatory action research (PAR). …”
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Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring by Giulia Trastulli, Giulia Calvino, Bruno Papasergi, Domenica Megalizzi, Cristina Peconi, Stefania Zampatti, Claudia Strafella, Carlo Caltagirone, Emiliano Giardina, Raffaella Cascella

“…These centers must be able to verify data quality and ensure sample integrity. This study aims at developing a protocol for tracking NGS-analyzed samples to prevent errors and mix-ups, ensuring proper quality control, accuracy, and reliability in genetic testing procedures. …”
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Enhanced Multi‐Objective Optimization Model for Bridge Performance Assessment and Prediction, Based on Improved PCA, K‐Means Clustering, and Kaplan–Meier Survival Algorithm by Chengzhong Gui, Zhi Duan, Zuwei Huang, Zhiguo Sun, Wei Qiao, Yu Cheng

“…The initial phase of the study concentrates on the diversification and decentralization of monitored data from various sources, integrating and cleaning data obtained from different sources to ensure data quality and consistency. PCA technique is applied to identify key sub‐parameters that have significant impacts on the performance of structural components. …”
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Psychosocial, physical, cognitive and quality of life aspects in primary restless legs syndrome by I. Jarašiūnaitė, R. Kaladytė-Lokominienė

“…Participants of the study were provided with a questionnaire pack, including International RLS Study Group scale (IRLSSGS), demographic data, quality of life scale SF-36, Hospital Anxiety and Depression Scale (HADS), Montreal Cognitive Assessment (MoCA), Epworth daytime sleepiness scale, and Fatigue questionnaire. …”
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Effect of PCSK9 Inhibitor on Blood Lipid Levels in Patients with High and Very-High CVD Risk: A Systematic Review and Meta-Analysis by Yue Zhang, Yanrong Suo, Lin Yang, Xiaolu Zhang, Qun Yu, Miao Zeng, Wenlan Zhang, Xijuan Jiang, Yijing Wang

“…Design. 14 trials (n = 52,586 patients) comparing treatment with or without PCSK9 inhibitors were retrieved from PubMed and Embase updated to 1st Jun 2021. The data quality of included studies was assessed by two independent researchers using the Cochrane systematic review method. …”
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Effectiveness of a personal health coaching intervention (diabetescoach) in patients with type 2 diabetes: protocol for an open-label, pragmatic randomised controlled trial by Oliver Faude, Fiona Streckmann, Lukas Zahner, Markus Gerber, Vivien Hohberg, Jan-Niklas Kreppke, Jan Kohl, Eleonora Seelig, Daniel König

“…Secondary outcomes are self-reported physical activity, nutrition, cognitive mediators of changes in sport-related behaviour, blood values, medication and nutritional supplements, anthropometric data, quality of life, neuropathy and cost-effectiveness. …”
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Early Detection of Multiwavelength Blazar Variability by Hermann Stolte, Jonas Sinapius, Iftach Sadeh, Elisa Pueschel, Matthias Weidlich, David Berge

“…The framework incorporates measurement uncertainties and is robust given data quality challenges, such as varying cadences and observational gaps. …”
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Big Data Governance Challenges Arising From Data Generated by Intelligent Systems Technologies: A Systematic Literature Review by Yunusa Adamu Bena, Roliana Ibrahim, Jamilah Mahmood, Arafat Al-Dhaqm, Ahmad Alshammari, Maged Nasser, Muhammed Nura Yusuf, Matthew O. Ayemowa

“…A synthesis of insights from 74 peer-reviewed articles, conferences, and industry reports reveals both the significant benefits of BDG such as enhanced decision-making, operational efficiency, and regulatory compliance and persistent challenges, including fragmented governance frameworks, limited scalability, data quality issues, and ethical concerns. To address these gaps, this study proposes the big data governance maturity assessment model (BDG MAM), a novel framework developed to assess and enhance the maturity of BDG programs. …”
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Implementation of a Laboratory Information Management System (LIMS) for microbiology in Timor-Leste: challenges, mitigation strategies, and end-user experiences by Tessa Oakley, Juliao Vaz, Fausto da Silva, Raikos Allan, Deonisia Almeida, Karen Champlin, Endang Soares da Silva, Ari Jayanti Tilman, Ian Marr, Heidi Smith-Vaughan, Jennifer Yan, Joshua R. Francis

“…The LIMS reduced transcription errors and standardised reporting of antimicrobial susceptibility testing (AST), improving data quality and accessibility. However, challenges such as unreliable internet connectivity and the need for ongoing funding and technical support persist. …”
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Barriers and facilitators to data-based decision making in Australian early childhood education and care: A qualitative study by Shauna Sherker, Karen Villanueva, Ruth Beatson, Caitlin M. Macmillan, Wan Yi Lee, Olivia Hilton, Carly Molloy, Sharon Goldfeld

“…Barriers spanned issues of capability (knowledge), opportunity (data systems and processes, data quality, data availability, resources) and motivation (data culture, trust, pressure). …”
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Clinical code usage in UK general practice: a cohort study exploring 18 conditions over 14 years by Christos Grigoroglou, Darren M Ashcroft, Evangelos Kontopantelis, David Reeves, Salwa S Zghebi, Rosa Parisi, Brian McMillan

“…Adopting more consistent and less diverse coding would help improve data quality in primary care. Future research is needed following the transfer to the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) coding.…”
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Can verbal autopsies be used on a national scale? Key findings and lessons from South Africa's national cause-of-death validation study by Monique Maqungo, Nadine Nannan, Beatrice Nojilana, Erin Nichols, Diane Morof, Mireille Cheyip, Chalapati Rao, Carl Lombard, Jessica Price, Kathleen Kahn, Lorna J. Martin, Francois Bezuidenhout, Ria Laubscher, Chodziwadziwa Kabudula, Tracy Glass, Oluwatoyin Awotiwon, Nesbert Zinyakatira, Noluntu Funani, Jané Joubert, Debbie Bradshaw, Pamela Groenewald

“…Feasibility was evaluated based on response rates, participation, and data quality. Results Of the total 36,976 deaths registered, only 26% were identified during recruitment, with a 55% overall response rate for VA interviews. …”
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Evaluations and calculations of neutron reactions on 238U up to 20 MeV by Yue Zhang, Ruirui Xu, Yuan Tian, Haicheng Wu, Xichao Ruan, Yinlu Han, Huanyu Zhang, Ping Liu, Xi Tao, Zhi Zhang, Changlin Lan, Xiaodong Sun, Yongli Jin, Nengchuan Shu, Jimin Wang, Xiaolong Huang, Zhigang Ge

“…Guided by integral benchmark, (n,inl), (n,γ) and (n,f) reaction cross sections have undergone multiple adjustments, leading to a noticeable improvement in data quality, as indicated by final benchmark results.…”
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Comprehensive approach to predictive analysis and anomaly detection for road crash fatalities by Chopparapu Gowthami, S. Kavitha

“…Through the possibility of highlighting regions with increased risk or problems with data quality, this part of the research improves our comprehension of unexpected events in accident data. …”
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Synthetic Data Generation and Evaluation Techniques for Classifiers in Data Starved Medical Applications by Wan D. Bae, Shayma Alkobaisi, Matthew Horak, Siddheshwari Bankar, Sartaj Bhuvaji, Sungroul Kim, Choon-Sik Park

“…We propose an incremental synthetic data generation system that improves data quality over iterations by gradually adjusting to the data distribution and thus avoids overfitting in classifiers. …”
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