System for digital character recognition, extraction and structuring of medical data with the formation of a cloud-based electronic health records by A. A. Komkov, V. P. Mazaev, S. V. Ryazanova, A. A. Kobak

“…The use of available systems for obtaining structured data from primary medical information is based on the use of various technologies, including digital transformation of primary data for the formation of electronic health records. …”
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A corrosion risk assessment method for underground gas storage ground pipeline based on data and knowledge dual drivers by BI Caixia

“…This article presents a risk assessment methodology that leverages data and knowledge fusion. The process begins with a statistical analysis of the corrosion failure data from ground process pipelines in underground gas storage facilities, from which a Bayesian corrosion prediction model is developed. …”
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Longitudinal Motion System Identification of a Fixed-Wing Unmanned Aerial Vehicle Using Limited Unplanned Flight Data by Nuno M. B. Matos, André C. Marta

“…This work delves into the application of system identification techniques on unplanned flight data when faced with a shortage of dedicated flight test data. …”
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A Bayesian network approach incorporating imputation of missing data enables exploratory analysis of complex causal biological relationships. by Richard Howey, Alexander D Clark, Najib Naamane, Louise N Reynard, Arthur G Pratt, Heather J Cordell

“…We show that this approach leads to marked improvements in the recall and precision of directed edges in the final network identified, and we illustrate the approach through application to data from a recent study investigating the causal relationship between methylation and gene expression in early inflammatory arthritis patients. …”
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Documentation for Architectural Heritage: A Historical Building Information Modeling Data Modeling Approach for the Valentino Castle North Wing by Xiang Li, Lorenzo Teppati Losè, Fulvio Rinaudo

“…Although HBIM (Historical Building Information Modeling) excels in geometric data acquisition and modeling within Scan-to-BIM (Building Information Modeling) workflows, its application in digital documentation faces persistent challenges, such as balancing precision and efficiency, ambiguous information structures, and the absence of standardized protocols. …”
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Rapid Determination of Six Low Molecular Carbonyl Compounds in Tobacco Smoke by the APCI-MS/MS Coupled to Data Mining by Wuduo Zhao, Qidong Zhang, Binbin Lu, Shihao Sun, Shusheng Zhang, Jianxun Zhang

“…The experimental results indicated that the established method had the potential application in rapid determination of low molecular carbonyl compounds.…”
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Spike Stall Precursor Detection in a Single-Stage Axial Compressor: A Data-Driven Dynamic Modeling Approach by Anish Thapa, Jichao Li, Marco P. Schoen

“…The autoregressive model is adaptively extracted from measured pressure data from a one-stage axial compressor test stand. …”
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On Explainability of Reinforcement Learning-Based Machine Learning Agents Trained with Proximal Policy Optimization That Utilizes Visual Sensor Data by Tomasz Hachaj, Marcin Piekarczyk

“…In this paper, we address the issues of the explainability of reinforcement learning-based machine learning agents trained with Proximal Policy Optimization (PPO) that utilizes visual sensor data. We propose an algorithm that allows an effective and intuitive approximation of the PPO-trained neural network (NN). …”
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Handling multiple time-varying exposures in survival analysis using real-world pediatric data from the pedianet database by E. Gonzato, L. Annicchiarico, A. Cantarutti, C. Di Chiara, V. Rigamonti, D. Valentini

“…To apply multiple time-varying approaches and to compare estimates derived from different models using an application with real-world data in the paediatric field. …”
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Robust Traffic Signal Retiming Based on Queue Service Time Estimation Using Low-Penetration Connected Vehicle Data by Chengchuan An, Weihua Zhang, Yinpu Wang, Siping Ke, Jingxin Xia

“…Previous studies have explored the potential of using connected vehicle data for signal retiming specifically under the current low-penetration environment, which will significantly reduce the cost and increase the productivity of signal retiming. …”
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Multimodal LLM for enhanced Alzheimer’s Disease diagnosis: Interpretable feature extraction from Mini-Mental State Examination data by Meiwei Zhang, Yuwei Pan, Qiushi Cui, Yang Lü, Weihua Yu

“…The Mini-Mental State Examination (MMSE) is widely used for initial screening, but its traditional application often underutilizes the rich multimodal data it generates, such as videos, images, and speech. …”
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A Proposed Deep Learning Framework for Air Quality Forecasts, Combining Localized Particle Concentration Measurements and Meteorological Data by Maria X. Psaropa, Sotirios Kontogiannis, Christos J. Lolis, Nikolaos Hatzianastassiou, Christos Pikridas

“…Both models used past particulate matter measurements alongside local meteorological data as inputs. The slideNN variable-depth architecture consists of a set of independent neural network models, referred to as strands. …”
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Multimodal data fusion for Alzheimer's disease based on dynamic heterogeneous graph convolutional neural network and generative adversarial network by Xiaoyu Chen, Shuaiqun Wang, Wei Kong

“…This study provides a novel and effective solution for the application of multi-modal data fusion in Alzheimer's disease classification.…”
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Mapping fruit tree dynamics using phenological metrics from optimal Sentinel-2 data and Deep Neural Network by Yingisani Chabalala, Elhadi Adam, Mahlatse Kganyago

“…The results demonstrate the potential of temporal phenological optical-based data in mapping fruit tree crops under different management systems. …”
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Analysis of Gene Expression Omnibus high-throughput sequencing data for the determination of microribonucleic acids in the blood plasma of patients with glioblastomas by A. A. Pushkin, D. Yu. Gvaldin, N. N. Timoshkina, E. E. Rostorguev, L. Yu. Vladimirova, E. A. Dzenkova

“…The study analyzed the data of 131 samples, where 35 samples with glioblastoma and 96 samples of the conditionally healthy group. …”
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Radiation Absorbed Dose Evaluation of [177Lu] Lu-DOTMP Radiopharmaceutical in Man Based On Biodistribution Data in Wistar Rats by Reza Bagheri, Hassan Ranjbar

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Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system by Muhammad Irfan, Nabeel Ahmed Khan, Muhammad Abubakar, Zohaib Mushtaq, Tomasz Jakubowski, Paweł Sokołowski, Grzegorz Nawalany, Saifur Rahman

“…The following study explores the application of Supervisory Control and Data Acquisition (SCADA) data for fault detection and diagnosing different operational states in wind turbines by focusing on environmental and operational factors which affect the performance. …”
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AI-MedLeafX: a large-scale computer vision dataset for medicinal plant diagnosisMendeley Data by Md. Fahim Ferdous, Faysal Bin Khaled Nissan, Nur Muhammad Nibir, Md. Hasan Imam Bijoy

“…The original dataset comprised 10,858 high-resolution images, which were subsequently expanded to 65,148 through the application of six comprehensive data augmentation techniques, including rotations (45°, 60°, and 90°), horizontal flipping, zooming and brightness adjustment. …”
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A revisiting of early 18th-century environmental data to identify Gulf of Lion properties before the industrial era by M. Locritani, S. Garvani, S. Garvani, G. Tamburello, A. Guarnieri, A. Guarnieri, G. Manzella

“…Nonetheless, understanding Marsili's findings is difficult due to the application of non-standard measurement units and the imprecision of georeferencing data. …”
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Improving Fall Classification Accuracy of Multi-Input Models Using Three-Axis Accelerometer and Heart Rate Variability Data by Seunghui Kim, Jae Eun Ko, Seungbin Baek, Daechang Kim, Sungmin Kim

“…Patterns were identified from the various movement characteristics of acceleration sensor data using a deep learning model consisting of CNN-LSTM, and heart rate variability (HRV) data were analyzed using a wide learning model to provide additional weight values for fall classification. …”
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