Transforming precision medicine: The potential of the clinical artificial intelligent single‐cell framework by Christian Baumgartner, Dagmar Brislinger

“…Despite its potential, caiSC lacks comprehensive data coverage across cell types and diseases, presenting challenges in data quality and model robustness. The article explores development strategies such as data expansion, machine learning advancements, and interpretability improvements. …”
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Advances in Biomedical Missing Data Imputation: A Survey by Miriam Barrabes, Maria Perera, Victor Novelle Moriano, Xavier Giro-I-Nieto, Daniel Mas Montserrat, Alexander G. Ioannidis

“…Missing values compromise data quality and can make it difficult to perform data-based studies. …”
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Open Data Release and Privacy Concerns: Complexity in Mitigating Vulnerability with Controlled Perturbation by Shah Imran Alam, Ihtiram Raza Khan, Syed Imtiyaz Hassan, Farheen Siddiqui, M. Afshar Alam, Anil Kumar Mahto

“…We discussed the gap and reported the benefits and loss with various combinations of K and l values, taken in combination with released data quality from an analyst’s perspective. We first used dummy fictitious data to explain the general expectations and then concluded the contrast in the findings with the real data from the food technology domain. …”
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Marketing Mix Implementation Strategy in Improving Teacher Performance: A Study at State Senior High Schools In Bandung City by Herty Ramayanti Sinaga

“…Validity, reliability, and normality tests confirm robust data quality. The results emphasize the importance of curriculum innovation, equitable incentives, and quality infrastructure in enhancing teacher performance. …”
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Design and Study of Data Application Sub-Layer of Smart Pipe System by Yafei Zhang, Dong Yan

“…With the gradual improvement of smart pipe system and the constant enrichment of its peripheral application system, higher requirements are raised for the data-providing capability and the data quality of the multidimensional awareness system. …”
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Centralized Big Data Management Model of Object-Oriented Process Driven by Qing Zhang

“…Along with big data era,the rapid data growth,large-scale parallel processing and access requirements of increasingly urgent,partition the domain data storage,processing and application architecture has been gradually formed.Enterprises are urgent to achieve full network data integration management,effective data application,guarantee the data quality,give full play to the value of data management.Therefore,a centralized big data management model of object-oriented process driven was proposed.The model uses a life cycle method to tease out several typical data objects,and through a standardized process to drive the collaborative management of data.…”
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Komparasi Kinerja Algoritma Blocking Pada Proses Indexing Untuk Deteksi Duplikasi by M. Miftakul Amin, Yevi Dwitayanti

“…Abstract   The process of integrating data from heterogeneous data sources requires good data quality. One of the characteristics of good data quality is avoiding data duplication. …”
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Developing Guidelines for Conducting Stigma Research With Transgender and Nonbinary Individuals: Protocol for Creation of a Trauma-Informed Approach to Research by Augustus Klein, Sarit A Golub, Danielle Berke, Elijah Castle

“…ConclusionsTo make meaningful strides in stigma research, it is imperative to examine experiences of stigma that may happen within the research context and identify strategies for improving data quality and reducing unintentional harm in study recruitment, methodology, implementation, and dissemination. …”
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Automated skin lesion detection and prevalence estimation in Tamanend's bottlenose dolphins by Colin J. Murphy, Melissa A. Collier, Ann-Marie Jacoby, Eric M. Patterson, Megan M. Wallen, Janet Mann, Shweta Bansal

“…On the other hand, we find that individual-level analyses from the model predictions may be more sensitive to data quality, and thus, some individual scale questions may not be feasible to address if data quality is inconsistent. …”
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De l’histoire numérique à l’histoire données ? by Cédric du Mouza, Stéphane Lamassé, Philippe Rygiel

“…From ongoing work, following on from previous undertakings, the authors show that a formalization of data that integrates the conditions of their production and a link to documentary apparatus, which is only possible thanks to effective collaboration with practitioners from other disciplines, enriches the interpretation of historical data while producing knowledge effects as to their nature and giving rise to fruitful questions for computer scientists relating to the consideration of data quality.…”
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Research on incentive mechanism for mobile intelligent edge computing by Shuyun LUO, Yuzhou WEN, Weiqiang XU, Shenghong ZHU

“…As a new architecture,mobile edge computing gives edge users stronger capabilities of computing,storage and communication,but it needs reasonable incentives mechanism to motivate edge users to provide resources.In terms of the three typical scenarios of mobile intelligent edge computing:computation offloading,edge caching and data collection,the incentive mechanism in the above scenarios was studied at first,then the core scientific problems were proposed that need to be solved in the incentive mechanism design of mobile intelligent edge computing from three perspectives of service quality,network quality and data quality.Finally,the technical challenges in the process of solving the above problems were analysed deeply and the corresponding feasible solutions were given.…”
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Historical Databases, Big and Small by Peter Doorn

“…Not only the volume of data defines if data is 'Big', but three more Vs characterise the term: velocity (speed of data generation and processing), veracity (referring to data quality) and variety. Perhaps the most defining is methodological: data becomes really big when new methods are needed to process and analyse it. …”
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Big Data Technology：Current Applications and Prospects by Jianxin Liao

“…The research includes computer science，information science，management science，psychology，etc.Four key technologies in big data research，data collection，preprocessing and storage，data analysis and mining，data privacy protection，data center system structure were discussed and the hot research topics from domestic and overseas research groups were demonstrated in order to have comprehensive and systematic understanding of big data.The application status of big data was introduced from three perspectives，application platforms，relevant products and standardization.Meanwhile，description of current business in big data and other field was presented.Eventually，the opportunities and challenges in big data research were revealed through big data analysis strategies，privacy protection and data quality，which provide the guideline for future research.…”
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Les observatoires de la mer et du littoral : du suivi des interactions hommes-milieux à la coordination des acteurs by Jean-Michel Salles, Hélène Rey Valette, Rémi Mongruel

“…In addition, it also addresses the issue of data quality and the legitimacy of the standards against which monitoring is carried out. …”
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Quality of routine malaria data captured at primary health facilities in the Hohoe Municipality, Ghana by Christopher Ayisah, Thywill Worlase Kpenu, Edem Kojo Dzantor, Clement Tetteh Narh

“…Although, half of the facilities showed evidence of good data quality, there is still a need for improvement in the capturing of routine malaria data.…”
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Insights gained through real-time monitoring of porcine reproductive and respiratory syndrome virus and description of temporal trends based on laboratory data in Ontario, Canada by Tatiana Petukhova, Maria Spinato, Tanya Rossi, Michele T. Guerin, Cathy A. Bauman, Pauline Nelson-Smikle, Davor Ojkic, Zvonimir Poljak

“…Most farms contributed one submission per week or per month for PRRSV testing (median: 1 submission per week; IQR: 0; max: 13; median: 1 submission per month; IQR: 1, max: 31). Epidemiological data quality showed considerable improvements over the 9 years of investigation. …”
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The assessment of routine health information system performance towards improvement of quality of reproductive, maternal, newborn, child and adolescent health services in Ondo and... by Victoria Oladoyin, Sunday Adedini, Kayode Ijadunola, Hassan Ogunwemimo, Olubunmi Folorunso, Elizabeth Chukwu, Ugo Okoli, Anthony Adoghe, Samuel Oyeniyi, Oniyire Adetiloye, Adesegun Fatusi

“…Performance of routine HMIS for RMNCAEH+N QoC in terms of data collection, data quality, and data use were analysed using univariate and bivariate statistics.…”
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An incentive mechanism with bandwidth allocation for federated learning by Yingyun GUO, Bo GAO, Zhifei ZHANG, Yu ZHANG, Ke XIONG

“…Federated learning (FL) is an emerging machine learning paradigm that can make full use of crowd sourced mobile resources for training on decentralized data.However, it is challenging to deploy FL over a wireless network because of the limited bandwidth and clients’ selfishness.To address these challenges, an incentive mechanism with bandwidth allocation (IMBA) was proposed.Considering the difference between clients' data quality and computing power, IMBA designs a payment scheme to incentivize high-quality clients to contribute their computing resources, thus improving the training accuracy of the model.By minimizing the weight sum of training time and payment cost, the optimal payment and bandwidth allocation scheme was determined, and the training delay was reduced by optimizing bandwidth allocation.Experiments show that IMBA effectively improves training accuracy, reduces the training delay and helps the server flexibly balance training delay and hiring payment.…”
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Epigenetic variation in light of population genetic practice by Sarah A. Mueller, Justin Merondun, Sonja Lečić, Jochen B. W. Wolf

“…Efforts to advance data quality, study design, and statistical treatment are encouraged to consolidate our understanding of the source of heritable epigenetic variation, quantify its autonomous potential for evolution, and enrich population genetic analyses with an additional layer of information.…”
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Development and application of a clinical core data set for deep brain stimulation in Parkinson’s disease, dystonia or tremor: from data collection to data exchange and data sharin... by Anna-Lena Hofmann, Jonas Widmann, Lilly Brandstetter, Udo Selig, Fabian Haug, Julian Haug, Rüdiger Pryss, Jasper Mecklenburg, Andrea Kreichgauer, Philipp Capetian, Christian J. Hartmann, Christian Niklas, Petra Ritter, Patricia Krause, Alfons Schnitzler, Jens Volkmann, Andrea A. Kühn, Peter Heuschmann, Kirsten Haas

“…The development followed standardized methodology comprising review of available evidence, a consensus process and performance of the first phase of the study. To ensure high data quality, measures for standardized training, monitoring as well as plausibility and data quality tests were implemented. …”
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