Enhancing healthcare data privacy and interoperability with federated learning by Adil Akhmetov, Zohaib Latif, Benjamin Tyler, Adnan Yazici

“…Despite advances in electronic medical records, mobile health applications, and wearable sensors, current digital health cannot fully exploit these data due to the lack of data analysis and exchange between heterogeneous systems. …”
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FONDUE—Fine-Tuned Optimization: Nurturing Data Usability & Efficiency by Valerie Restat, Indra Diestelkämper, Meike Klettke, Uta Störl

“…As a first building block of FONDUE, we present CheDDaR, which is used to detect errors and measure data quality. Both are important tasks for improving data quality with FONDUE.…”
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Listen to genes: dealing with microarray data in the frequency domain. by Jianfeng Feng, Dongyun Yi, Ritesh Krishna, Shuixia Guo, Vicky Buchanan-Wollaston

“…<h4>Background</h4>We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes.…”
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ZTCloudGuard: Zero Trust Context-Aware Access Management Framework to Avoid Medical Errors in the Era of Generative AI and Cloud-Based Health Information Ecosystems by Khalid Al-hammuri, Fayez Gebali, Awos Kanan

“…This article proposes a zero-trust-based context-aware framework for managing access to the main components of the cloud ecosystem, including users, devices, and output data. The main goal and benefit of the proposed framework is to build a scoring system to prevent or alleviate medical errors while using distributed medical devices in cloud-based healthcare information systems. …”
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Investigating the Relationship Between Liquidity Risk, Credit Risk, and Solvency Risk in Banks Listed on the Iranian Capital Market: A Panel Vector Error Correction Model by Pejman Peykani, Mostafa Sargolzaei, Cristina Tanasescu, Seyed Ehsan Shojaie, Hamidreza Kamyabfar

“…This study addresses a critical gap in the literature by examining the dynamic interrelationships among these three types of risk in the context of emerging markets. Using data from 21 banks listed on the Iranian capital market from 2011 to 2023, we employ a Panel Vector Error Correction Model (VECM) alongside panel impulse response analysis to assess both short- and long-term dynamics. …”
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Deciding which is the best ${}^1\protect \text{H}$ NMR predictor for organic compounds using statistical tools by Mah, Wern Huay, Ahmad Nazuan, Nadzran Hafiy, Yeap, Wei Sheung, Fakharudin, Farah Hasyeena, Faye, Ibrahima, Wilfred, Cecilia Devi

“…Root mean square deviation (RMSD) and mean absolute percentage error (MAPE) were calculated from the data obtained. …”
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Evaluation of Plaid Models in Biclustering of Gene Expression Data by Hamid Alavi Majd, Soodeh Shahsavari, Ahmad Reza Baghestani, Seyyed Mohammad Tabatabaei, Naghme Khadem Bashi, Mostafa Rezaei Tavirani, Mohsen Hamidpour

“…Biclustering algorithms for the analysis of high-dimensional gene expression data were proposed. …”
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DATA COMPRESSION USING WAVELET TRANSFORM IN BIOTELEMETRY SYSTEMS by O.E. Bezborodova, A.Yu. Bodin, O.N. Bodin, M.N. Kramm, D.V. Martynov

“…For a biotelemetric system as a radio engineering and information-measuring system, the main indicators are measurement error and reliability of data transmission. Materials and methods. …”

Improving Deep Learning for Forecasting Accuracy in Financial Data by Shih-Lin Lin, Hua-Wei Huang

“…This study uses an LSTM model for analysis of financial data, followed by a comparison of the analytical results with the actual data to see which has a larger root-mean-square-error (RMSE). …”
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Data on effect of NPSB fertilizer rates on growth and yield of carrot (Daucus carrota L.) varieties in Gondar district, Northwestern EthiopiaMendeley Data by Abebaw Mulugeta Andualem, Yenus Ousman Kemal, Derajew Asres Mekonen, Fentahun Asrat Yenet, Hulushum Woreta Kassa

“…Treatment consisted of NPSB nutrient levels (0:0:0:0, 21.3:15.3:2.80:0.04, 42.6:30.6:5.60:0.08, 64:46:8.41:0.12, 85.3:61.2:11.2:0.16, and 106.7:76.7:14.03:0.20 kg ha−1), which were laid out in a randomized complete block design with three replications. Data were collected on crop phenology, growth and root yield (marketable, unmarketable, and total root yield) parameters and subjected to analysis of variance using SAS computer software version 9.4. …”
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Estimation of Reference Crop Evapotranspiration in the Yellow River Basin Based on Machine Learning and Its Regional and Drought Adaptability Analysis by Jun Zhao, Huayu Zhong, Congfeng Wang

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Adding Data Quality to Federated Learning Performance Improvement by Ernesto Gurgel Valente Neto, Solon Alves Peixoto, Valderi Reis Quietinho Leithardt, Juan Francisco de Paz Santana, Julio C. S. Dos Anjos

“…Massive data generation from Internet of Things (IoT) devices increases the demand for efficient data analysis to extract relevant and actionable insights. …”
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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

“…The origins of missing values in biomedical datasets are diverse, including experimental errors, equipment malfunctions, and variations in data collection protocols tailored to individual patient conditions. …”
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ON AUTOMATED QUALITY CONTROL OF GEOPHYSICAL WELL LOGGING DATA by Roman Victorovich Pelmegov, Artem Georgiyevich Kudelin

“…The need for automated detection of errors and quality control of the recorded data during or immediately upon completion of studies is discussed. …”
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Application of educational data mining in subject learning at university by Irina A. Kotiurova

“…However, the described examples of practical use of educational data analysis not for university management, but for specific subject teaching are yet limited. …”
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TCGADownloadHelper: simplifying TCGA data extraction and preprocessing by Alexandra Anke Baumann, Alexandra Anke Baumann, Olaf Wolkenhauer, Olaf Wolkenhauer, Olaf Wolkenhauer, Markus Wolfien, Markus Wolfien

“…By establishing a clear step-by-step approach, we provide a streamlined methodology that minimizes errors, enhances data usability, and supports the broader utilization of TCGA data in cancer research. …”
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Wastewater-based epidemiology: deriving a SARS-CoV-2 data validation method to assess data quality and to improve trend recognition by Cristina J. Saravia, Peter Pütz, Christian Wurzbacher, Anna Uchaikina, Jörg E. Drewes, Ulrike Braun, Claus Gerhard Bannick, Nathan Obermaier

“…Furthermore, we investigated outliers in the ratio of the analysed gene segments that might indicate laboratory errors. To evaluate the success of our method, we measure the degree of accordance between identified QCP outliers and outliers in the SARS-CoV-2 concentration curves.Results and discussionOur analysis reveals that the flow and gene segment ratios are typically best at identifying outliers in the SARS-CoV-2 concentration curve albeit variations across WWTPs and laboratories. …”
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Automatic plant disease detection using computationally efficient convolutional neural network by Muhammad Rizwan, Samina Bibi, Sana Ul Haq, Muhammad Asif, Tariqullah Jan, Mohammad Haseeb Zafar

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ELECTRONIC JOURNAL OF EXPERIMENTS FOR ELECTRIC ARC REACTOR by Roman D. Gerasimov, Arseny D. Starikov, Alexander Ya. Pak

“…A modern solution is the development of a software package that automates the collection and transfer of data into electronic form, which also reduces the number of errors associated with the human factor. …”
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A Machine Learning-Based Intelligent Framework for Predicting Energy Efficiency in Next-Generation Residential Buildings by Hafiz Muhammad Shakeel, Shamaila Iram, Richard Hill, Hafiz Muhammad Athar Farid, Akbar Sheikh-Akbari, Farrukh Saleem

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