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Journal articles on the topic 'Progressive data analysis'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

P, Veeramuthu. "Analysis of Progressive Duplicate Data Detection." Journal of Computational Mathematica 3, no. 2 (2019): 41–50. http://dx.doi.org/10.26524/cm53.

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Rinzivillo, Salvatore, Dino Pedreschi, Mirco Nanni, Fosca Giannotti, Natalia Andrienko, and Gennady Andrienko. "Visually driven analysis of movement data by progressive clustering." Information Visualization 7, no. 3-4 (2008): 225–39. http://dx.doi.org/10.1057/palgrave.ivs.9500183.

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The paper investigates the possibilities of using clustering techniques in visual exploration and analysis of large numbers of trajectories, that is, sequences of time-stamped locations of some moving entities. Trajectories are complex spatio-temporal constructs characterized by diverse non-trivial properties. To assess the degree of (dis)similarity between trajectories, specific methods (distance functions) are required. A single distance function accounting for all properties of trajectories, (1) is difficult to build, (2) would require much time to compute, and (3) might be difficult to und

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Lee, Kyeong-Jun, Jae-Ik Lee, and Chan-Keun Park. "Analysis of generalized progressive hybrid censored competing risks data." Journal of the Korean Society of Marine Engineering 40, no. 2 (2016): 131–37. http://dx.doi.org/10.5916/jkosme.2016.40.2.131.

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Wang, Tao, Lianbin Deng, Yuhong Li, and Hao Peng. "Progressive TIN Densification with Connection Analysis for Urban Lidar Data." Photogrammetric Engineering & Remote Sensing 87, no. 3 (2021): 205–13. http://dx.doi.org/10.14358/pers.87.3.207.

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Urban lidar data are advantageous for capturing the terrain surface of built-up areas, which can be directly used to provide digital surface models. Cloud points are classified into ground points to obtain digital terrain models. This study proposes a method to improve the progressive triangulated irregular network (TIN ) densification method using a TIN connection analysis algorithm, namely, connection analysis via slope analysis. The proposed method comprises five steps: selection of seed points, connection and slope analysis, increasing the seed points, construction of the TIN model of the

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Hassan, Amal S., Rana M. Mousa, and Mahmoud H. Abu-Moussa. "Analysis of Progressive Type-II Competing Risks Data, with Applications." Lobachevskii Journal of Mathematics 43, no. 9 (2022): 2479–92. http://dx.doi.org/10.1134/s1995080222120149.

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Azarang, Leyla, and Manuel,Oviedo,de,la Fuente. "idmTPreg: Regression Model for Progressive Illness Death Data." R Journal 10, no. 2 (2019): 317. http://dx.doi.org/10.32614/rj-2018-081.

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M J, Sudhamani. "A Comprehensive Analysis of Cirrhosis Progression through Clinical Data." Power System Technology 49, no. 1 (2025): 784–801. https://doi.org/10.52783/pst.1622.

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Cirrhosis is a progressive liver disease characterized by liver fibrosis and scarring, which can eventually lead to liver failure. It is primarily caused by chronic alcohol con- sumption, viral hepatitis, and non-alcoholic fatty liver disease (NAFLD). Early detection and diagnosis are crucial for pre- venting the progression of the disease. Recent advancements in machine learning and deep learning techniques have shown great promise in enhancing the diagnostic accuracy of cirrhosis through non-invasive methods, such as medical imaging analysis and biomarker prediction. These techniques aid in

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Ravikumar, Ananya. "Exploring Parkinsons Disease Progression Through Python-Based Data Analysis Techniques." International Journal for Research in Applied Science and Engineering Technology 13, no. 6 (2025): 3344–49. https://doi.org/10.22214/ijraset.2025.72823.

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Parkinson’s disease is a long-term neurological illness that mainly influences motor functions balance, and speaking abilities. This study aims to present a reproducible Python-based EDA framework to understand the progressive growth of Parkinson’s disease using an authentic dataset comprising500affectedpatients. Withtheuseofmajorpython libraries, ExploratoryDataAnalysis(EDA)methodswereappliedtoclean,processandvisualizethedata.Thestudyinvolvedexploring correlation between features like UPDRS score, motor function, speech difficulty and years since diagnosis. Descriptive statistics, correlation

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Koch, Marcus W., Jop Mostert, Bernard Uitdehaag, and Gary Cutter. "Clinical outcome measures in SPMS trials: An analysis of the IMPACT and ASCEND original trial data sets." Multiple Sclerosis Journal 26, no. 12 (2019): 1540–49. http://dx.doi.org/10.1177/1352458519876701.

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Background: Still too little is known about the natural history of clinical outcome measures beyond the Expanded Disability Status Scale (EDSS), such as the timed 25-foot walk (T25FW) and nine-hole peg test (9HPT) in secondary progressive multiple sclerosis (SPMS). Objective: To describe progression on the EDSS, T25FW, 9HPT, and their combinations. To investigate the association of the baseline characteristics age, sex, EDSS, T25FW, gadolinium-enhancing lesions, and relapse activity with EDSS and T25FW progression. Methods: Using original trial data from the placebo arms of the IMPACT and ASCE

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Turkay, Cagatay, Erdem Kaya, Selim Balcisoy, and Helwig Hauser. "Designing Progressive and Interactive Analytics Processes for High-Dimensional Data Analysis." IEEE Transactions on Visualization and Computer Graphics 23, no. 1 (2017): 131–40. http://dx.doi.org/10.1109/tvcg.2016.2598470.

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Shilpa, Author, and Sunita Parashar. "Performance Analysis of Apriori Algorithm with Progressive Approach for Mining Data." International Journal of Computer Applications 31, no. 1 (2011): 13–18. http://dx.doi.org/10.5120/3788-5216.

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Al-Hossain, Abdullah Y. "Predictive Inference from the Exponentiated Weibull Model Given Adaptive Progressive Censored Data." Applied Mathematics & Information Sciences 10, no. 3 (2016): 1177–84. http://dx.doi.org/10.18576/amis/100336.

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Barrat, Sabine, and Salvatore Tabbone. "A Progressive Learning Method for Symbol Recognition." JUCS - Journal of Universal Computer Science 14, no. (2) (2008): 224–36. https://doi.org/10.3217/jucs-014-02-0224.

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This paper deals with a progressive learning method for symbol recognition which improves its own recognition rate when new symbols are recognized in graphic documents. We propose a discriminant analysis method which provides allocation rules from a training set of labelled data. However a discriminant analysis method is efficient only if the training set and the test data are defined in the same conditions but it is rare in real life. In order to overcome this problem, a conditional vector is added to each instance to take into account the parasitic effects between the test data and the train

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Alotaibi, Refah, Ehab M. Almetwally, and Hoda Rezk. "Reliability Analysis of Kavya Manoharan Kumaraswamy Distribution under Generalized Progressive Hybrid Data." Symmetry 15, no. 9 (2023): 1671. http://dx.doi.org/10.3390/sym15091671.

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Generalized progressive hybrid censoring approaches have been developed to reduce test time and cost. This paper investigates the difficulties associated with estimating the unobserved model parameters and the reliability time functions of the Kavya Manoharan Kumaraswamy (KMKu) distribution based on generalized type-II progressive hybrid censoring using classical and Bayesian estimation techniques. The frequentist estimators’ normal approximations are also used to construct the appropriate estimated confidence intervals for the unknown parameter model. Under symmetrical squared error loss, ind

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DE WIT, ASTRID, PETER PETRÉ, and FRANK BRISARD. "Standing out with the progressive." Journal of Linguistics 56, no. 3 (2020): 479–514. http://dx.doi.org/10.1017/s0022226719000501.

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In this paper we demonstrate on the basis of diachronic and synchronic data from a variety of languages that progressives are particularly liable to be used for the expression of extravagance. We define extravagant language use as a signaling mechanism that consists in the exploitation of an unconventional construction in a given context as a way for speakers to indicate that there is something non-canonical about the situation that they are reporting. Novel constructions naturally lend themselves to such extravagant exploitation, since they are by definition to a certain extent unconventional

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Elshahhat, Ahmed, Vikas Kumar Sharma, and Heba S. Mohammed. "Statistical analysis of progressively first-failure-censored data via beta-binomial removals." AIMS Mathematics 8, no. 9 (2023): 22419–46. http://dx.doi.org/10.3934/math.20231144.

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<abstract><p>Progressive first-failure censoring has been widely-used in practice when the experimenter desires to remove some groups of test units before the first-failure is observed in all groups. Practically, some test groups may haphazardly quit the experiment at each progressive stage, which cannot be determined in advance. As a result, in this article, we propose a progressively first-failure censored sampling with random removals, which allows the removal of the surviving group(s) during the execution of the life test with uncertain probability, called the beta-binomial pro

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Elshahhat, Ahmed, and Mazen Nassar. "Bayesian survival analysis for adaptive Type-II progressive hybrid censored Hjorth data." Computational Statistics 36, no. 3 (2021): 1965–90. http://dx.doi.org/10.1007/s00180-021-01065-8.

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Mohammed, Heba S., Mazen Nassar, Refah Alotaibi, and Ahmed Elshahhat. "Analysis of Adaptive Progressive Type-II Hybrid Censored Dagum Data with Applications." Symmetry 14, no. 10 (2022): 2146. http://dx.doi.org/10.3390/sym14102146.

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In life testing and reliability studies, obtaining whole data always takes a long time and lots of monetary and human resources. In this case, the experimenters prefer to gather data using censoring schemes that make a balance between the length of the test, the desired sample size, and the cost. Lately, an adaptive progressive type-II hybrid censoring scheme is suggested to enhance the efficiency of the statistical inference. By utilizing this scheme, this paper seeks to investigate classical and Bayesian estimations of the Dagum distribution. The maximum likelihood and Bayesian estimation me

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Helu, Amal, and Hani Samawi. "Statistical Analysis Based on Adaptive Progressive Hybrid Censored Data From Lomax Distribution." Statistics, Optimization & Information Computing 9, no. 4 (2021): 789–808. http://dx.doi.org/10.19139/soic-2310-5070-1330.

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In this article, we consider statistical inferences about the unknown parameters of the Lomax distribution basedon the Adaptive Type-II Progressive Hybrid censoring scheme, this scheme can save both the total test time and the cost induced by the failure of the units and increases the efficiency of statistical analysis. The estimation of the parameters is derived using the maximum likelihood (MLE) and the Bayesian procedures. The Bayesian estimators are obtained based on the symmetric and asymmetric loss functions. There are no explicit forms for the Bayesian estimators, therefore, we propose

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Staab, Jennifer M., Thomas M. O'Connell, and Shawn M. Gomez. "Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS)." BMC Bioinformatics 11, no. 1 (2010): 123. http://dx.doi.org/10.1186/1471-2105-11-123.

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Zhao, Hanqing, Huijun Zhang, Yan Liu, Yongzhen Zhang, and Xiaolong (Luke) Zhang. "Pattern discovery: A progressive visual analytic design to support categorical data analysis." Journal of Visual Languages & Computing 43 (December 2017): 42–49. http://dx.doi.org/10.1016/j.jvlc.2017.05.004.

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Noori Asl, M., R. Arabi Belaghi, and H. Bevrani. "On Burr XII Distribution Analysis Under Progressive Type-II Hybrid Censored Data." Methodology and Computing in Applied Probability 19, no. 2 (2016): 665–83. http://dx.doi.org/10.1007/s11009-016-9514-7.

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23

Horáková, Dana, Aaron Boster, Antonio Bertolotto, et al. "Proportion of alemtuzumab-treated patients converting from relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis over 6 years." Multiple Sclerosis Journal - Experimental, Translational and Clinical 6, no. 4 (2020): 205521732097213. http://dx.doi.org/10.1177/2055217320972137.

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Background Few data exist concerning conversion to secondary progressive MS in patients treated with disease-modifying therapies. Objective Determine the proportion of alemtuzumab-treated patients converting from relapsing-remitting to secondary progressive MS during the CARE-MS core and extension studies. Methods Patients ( N = 811) were analyzed post hoc for secondary progressive MS conversion. Optimal conversion definition: Expanded Disability Status Scale (EDSS) score ≥4, pyramidal functional system score ≥2, and confirmed progression over ≥3 months including confirmation within the functi

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Ahmed, Naveed, JeeWoong Park, Cristian Arteaga, and Haroon Stephen. "Investigation of Progressive Learning within a Statics Course: An Analysis of Performance Retention, Critical Topics, and Active Participation." Education Sciences 13, no. 6 (2023): 576. http://dx.doi.org/10.3390/educsci13060576.

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Previous research has demonstrated a link between prior knowledge and student success in engineering courses. However, while course-to-course relations exist, researchers have paid insufficient attention to internal course performance development. This study aims to address this gap—designed to quantify and thus extract meaningful insights—by examining a fundamental engineering course, Statics, from three perspectives: (1) progressive learning reflected in performance retention throughout the course; (2) critical topics and their influence on students’ performance progression; and (3) student

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Abd El-Raheem, Abd El-Raheem M., Mona Hosny, and Mahmoud H. Abu-Moussa. "On Progressive Censored Competing Risks Data: Real Data Application and Simulation Study." Mathematics 9, no. 15 (2021): 1805. http://dx.doi.org/10.3390/math9151805.

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Competing risks are frequently overlooked, and the event of interest is analyzed with conventional statistical techniques. In this article, we consider the analysis of bi-causes of failure in the context of competing risk models using the extension of the exponential distribution under progressive Type-II censoring. Maximum likelihood estimates for the unknown parameters via the expectation-maximization algorithm are obtained. Moreover, the Bayes estimates of the unknown parameters are approximated using Tierney-Kadane and MCMC techniques. Interval estimates using Bayesian and classical techni

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Ricks, Trenton M., Evan J. Pineda, Brett A. Bednarcyk, et al. "Multiscale Progressive Failure Analysis of 3D Woven Composites." Polymers 14, no. 20 (2022): 4340. http://dx.doi.org/10.3390/polym14204340.

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Application of three-dimensional (3D) woven composites is growing as an alternative to the use of ply-based composite materials. However, the design, analysis, modeling, and optimization of these materials is more challenging due to their complex and inherently multiscale geometries. Herein, a multiscale modeling procedure, based on efficient, semi-analytical micromechanical theories rather than the traditional finite element approach, is presented and applied to a 3D woven carbon–epoxy composite. A crack-band progressive damage model was employed for the matrix constituent to capture the glob

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Ralovich, K., J. Zhang, S. K. Zhou, D. Comaniciu, and M. Sofka. "Progressive Data Transmission for Anatomical Landmark Detection in a Cloud." Methods of Information in Medicine 51, no. 03 (2012): 268–78. http://dx.doi.org/10.3414/me11-02-0017.

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SummaryBackground: In the concept of cloud-computing-based systems, various authorized users have secure access to patient records from a number of care delivery organizations from any location. This creates a growing need for remote visualization, advanced image processing, state-of-the-art image analysis, and computer aided diagnosis.Objectives: This paper proposes a system of algorithms for automatic detection of anatomical landmarks in 3D volumes in the cloud computing environment. The system addresses the inherent problem of limited bandwidth between a (thin) client, data center, and data

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Mohammed, Heba S., Osama Abo-Kasem, and Ahmed Elshahhat. "Optimum Progressive Data Analysis and Bayesian Inference for Unified Progressive Hybrid INH Censoring with Applications to Diamonds and Gold." Axioms 14, no. 8 (2025): 559. https://doi.org/10.3390/axioms14080559.

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A novel unified progressive hybrid censoring is introduced to combine both progressive and hybrid censoring plans to allow flexible test termination either after a prespecified number of failures or at a fixed time. This work develops both frequentist and Bayesian inferential procedures for estimating the parameters, reliability, and hazard rates of the inverted Nadarajah–Haghighi lifespan model when a sample is produced from such a censoring plan. Maximum likelihood estimators are obtained through the Newton–Raphson iterative technique. The delta method, based on the Fisher information matrix

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Balabaeva, E. A., O. L. Fabrikantov, and I. Y. Sharapov. "A comparative analysis of orthokerathology correction efficiency in children with progressive myopia." Reflection 18, no. 2 (2024): 25–28. https://doi.org/10.25276/2686-6986-2024-2-25-28.

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Purpose. To analyze stabilization of myopia when using orthokeratological lenses in children of different age groups. Methods. We have conducted a retrospective analysis of medical records of 146 school age children aged 6 to 16 years with progressive mild and moderate myopia. Follow-up period was 3 years (2020–2022). Results. A significant proportion of myopia progression was identified in children using monofocal glasses, ranging from 59 to 90 % depending on age according to biometry data. According to refractometry data, progression of more than 1 diopter per year was noted in 70–71.8 % of

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Meng, Yang, Grant McCarthy, Anthony Berthon, and Jerome Dinet. "VP133 Patient-Reported Health State Utilities In Neuroendocrine Tumours." International Journal of Technology Assessment in Health Care 33, S1 (2017): 210. http://dx.doi.org/10.1017/s0266462317003828.

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INTRODUCTION:Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are rare cancers most often found in the gastrointestinal system or the pancreas. However, patient-reported health state utilities based on clinical trials have not been previously reported in this disease area.METHODS:The CLARINET study collected the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 data from patients in both stable and progressive disease states, although data for the latter were only available during the early stage of progression due to trial design. Using published algorithms, d

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Akash, Mehta, Datta Bhanu, Saha Biswajit, Viswanathan Deepthi, and M.P Sahana. "Data Analysis as an Online Tool." Journal of Data Mining and Management 4, no. 2 (2019): 21–24. https://doi.org/10.5281/zenodo.3335927.

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<em>The emergence of Data analysis and Internet of Things (IOT) has now established a foundation for representing and storing data from domains ranging from smart devices to smart cities. The data collected using sensor from IOT has been made available to the public and has helped a huge number of consumers of data to utilize such data sets for several applications starting from scientific experimentation and modulation to improving commercial activity forbusinesses.Following this has resulted in the requirement for the developing data analysis tools that ease the use for customers and allocat

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Pasupuleti, Murali Krishna. "Topological Data Analysis for Early Detection of Neurodegenerative Disease." International Journal of Academic and Industrial Research Innovations(IJAIRI) 05, no. 04 (2025): 267–77. https://doi.org/10.62311/nesx/rp2225.

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Abstract: Neurodegenerative diseases, such as Alzheimer's and Parkinson's, are characterized by progressive neuronal deterioration, leading to cognitive and motor impairments. Early detection is crucial for effective intervention and management. This study proposes a novel framework utilizing Topological Data Analysis (TDA), particularly persistent homology, to identify early biomarkers from neuroimaging and physiological data. This study explores the application of TDA techniques—specifically persistent homology and topological invariants—for the early detection of neurodegenerative diseases

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Foley, Hannah, Louise Jarrett, and Timothy Harrower. "Understanding progression in multiple sclerosis: analysis of an in-patient admissions audit." British Journal of Neuroscience Nursing 20, Sup4 (2024): S16—S24. http://dx.doi.org/10.12968/bjnn.0024.

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Analysis of in-patient data is valuable to reduce avoidable admissions, which are disruptive to patients and costly to the NHS. The audit aimed to identify causes of in-patient admissions of people with multiple sclerosis at a district general hospital. The audit comprised a retrospective evaluation of secondary in-patient admissions data. Primary causes of admissions included chest infections, falls and urinary tract infections. Secondary progressive multiple sclerosis accounted for the largest number of admissions by multiple sclerosis sub-type, disproportionate to representation on the mult

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Foley, Hannah, Louise Jarrett, and Timothy Harrower. "Understanding progression in multiple sclerosis: analysis of an in-patient admissions audit." British Journal of Neuroscience Nursing 20, Sup4 (2024): S16—S24. http://dx.doi.org/10.12968/bjnn.2024.0004.

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Analysis of in-patient data is valuable to reduce avoidable admissions, which are disruptive to patients and costly to the NHS. The audit aimed to identify causes of in-patient admissions of people with multiple sclerosis at a district general hospital. The audit comprised a retrospective evaluation of secondary in-patient admissions data. Primary causes of admissions included chest infections, falls and urinary tract infections. Secondary progressive multiple sclerosis accounted for the largest number of admissions by multiple sclerosis sub-type, disproportionate to representation on the mult

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Zhu, J., Z. Zhang, X. Hu, and Z. Li. "ANALYSIS AND APPLICATION OF LIDAR WAVEFORM DATA USING A PROGRESSIVE WAVEFORM DECOMPOSITION METHOD." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-5/W12 (September 3, 2012): 31–36. http://dx.doi.org/10.5194/isprsarchives-xxxviii-5-w12-31-2011.

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van Riel, Natal A. W., Christian A. Tiemann, Joep Vanlier, and Peter A. J. Hilbers. "Applications of analysis of dynamic adaptations in parameter trajectories." Interface Focus 3, no. 2 (2013): 20120084. http://dx.doi.org/10.1098/rsfs.2012.0084.

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Metabolic profiling in combination with pathway-based analyses and computational modelling are becoming increasingly important in clinical and preclinical research. Modelling multi-factorial, progressive diseases requires the integration of molecular data at the metabolome, proteome and transcriptome levels. Also the dynamic interaction of organs and tissues needs to be considered. The processes involved cover time scales that are several orders of magnitude different. We report applications of a computational approach to bridge the scales and different levels of biological detail. Analysis of

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Procopio, Marianne, Carlos Scheidegger, Eugene Wu, and Remco Chang. "Selective Wander Join: Fast Progressive Visualizations for Data Joins." Informatics 6, no. 1 (2019): 14. http://dx.doi.org/10.3390/informatics6010014.

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Progressive visualization offers a great deal of promise for big data visualization; however, current progressive visualization systems do not allow for continuous interaction. What if users want to see more confident results on a subset of the visualization? This can happen when users are in exploratory analysis mode but want to ask some directed questions of the data as well. In a progressive visualization system, the online aggregation algorithm determines the database sampling rate and resulting convergence rate, not the user. In this paper, we extend a recent method in online aggregation,

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McGlynn, Mary Claire, Mohammad H. Abu-Arja, Sumanth Nagabushan, et al. "RARE-08. MULTI-INSTITUTIONAL ANALYSIS OF PEDIATRIC RELAPSED/REFRACTORY CENTRAL NERVOUS SYSTEM GERMINOMA." Neuro-Oncology 25, Supplement_1 (2023): i35. http://dx.doi.org/10.1093/neuonc/noad073.137.

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Abstract BACKGROUND Relapsed central nervous system (CNS) germinomas are rare with no universal agreement regarding management. We explore prognostic factors that may impact the treatment of patients with relapsed CNS germinoma. METHODS An international multi-institutional retrospective study of relapsed/progressive CNS germinomas was conducted. Data was summarized using descriptive statistics. Overall survival (OS) was evaluated using Kaplan-Meier and Fischer’s exact test to estimate odds ratios (OR) and 95% confidence intervals (CI). RESULTS Analysis included 21 patients (Male 71.4%) with re

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Puente, I., R. Lindenbergh, A. Van Natijne, R. Esposito, and R. Schipper. "MONITORING OF PROGRESSIVE DAMAGE IN BUILDINGS USING LASER SCAN DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 923–29. http://dx.doi.org/10.5194/isprs-archives-xlii-2-923-2018.

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Vulnerability of buildings to natural and man-induced hazards has become a main concern for our society. Ensuring their serviceability, safety and sustainability is of vital importance and the main reason for setting up monitoring systems to detect damages at an early stage. In this work, a method is presented for detecting changes from laser scan data, where no registration between different epochs is needed. To show the potential of the method, a case study of a laboratory test carried out at the Stevin laboratory of Delft University of Technology was selected. The case study was a quasi-sta

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YEHOSHYNA, H. A., S. M. VORONOY, O. I. POLIKAROVSKYKH, and R. O. GOKHMAN. "INTERFACES SIMILARITY ANALYSIS FOR PROGRESSIVE WEB APPS AND WEB-APPLICATIONS BASED ON DISTILBERT TRANSFORMER." Scientific papers of Donetsk National Technical University. Series: Informatics, Cybernetics and Computer Science 2 - №1, no. 35-36 (2023): 51–60. http://dx.doi.org/10.31474/1996-1588-2023-1-36-51-60.

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An approach to automated testing of components of Progressive Web Applications interfaces by determining their relevance to elements of the corresponding web versions of applications is proposed. An analysis of modern trends and existing categories in the field of Web Mining was carried out. It is shown that the predominant trend in the analysis of the interface structures of modern web applications is the use of Deep Learning technologies. Features and functioning of the latest Transformers neural network architecture are considered. The choice of the Transformers type model to determine the

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Aminat, Suleman-Alabi, Fauzah Abd Ghani, Nor Fadhlina Zakaria, Malina Osman, and Rafidah Hod. "Immunoglobulin A Nephropathy: A 10-year Analysis in a Single Malaysian Centre." BMSC 19, s12 (2023): 29–37. http://dx.doi.org/10.47836/mjmhs.19.s12.5.

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Introduction: Immunoglobulin A nephropathy (IgAN), also referred to as Berger’s disease, is the leading primary glomerular disease cause of end-stage kidney disease (ESKD). Its prevalence, presentation, and progression have been shown to vary between different regions and ethnicities. This study aims to explore the presentation, predictors of disease progression, and outcome in a cohort of Malaysian patients with IgAN. Methods: This study evaluated retrospective data from 82 patients with renal biopsy-proven IgAN. The patients were classified into two categories based on their estimated glomer

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Madan Kumar, K. M. V., and B. Srinivasa Rao. "Mining Frequent Utility Sequential Patterns in Progressive Databases by U-Pisa." Journal of Computational and Theoretical Nanoscience 17, no. 4 (2020): 1786–95. http://dx.doi.org/10.1166/jctn.2020.8442.

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Sequential pattern mining is one of the most important aspects of data mining world and has a significant role in many applications like market analysis, biomedical analysis, weather forecasting etc. In the category of mining sequential patterns the usage of progressive database as an input database is relatively new and has a wide impact in decision-making system. In progressive sequential pattern mining, we discover the frequent sequences progressively with the help of period of Interest. As the traditional approaches of frequency based framework are not much more informative for decision ma

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Jung, Jaeyong, Dong Sik Kim, Beom Jin Chung, and Young Mo Chung. "Analysis on the Residential Progressive and Time-of-use Rates based on AMI Data." Journal of the Institute of Electronics and Information Engineers 58, no. 9 (2021): 66–77. http://dx.doi.org/10.5573/ieie.2021.58.9.66.

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Nassar, Mazen Mohammed, and Samir Kamel Ashour. "Analysis of Exponential Distribution Under Adaptive Type-I Progressive Hybrid Censored Competing Risks Data." Pakistan Journal of Statistics and Operation Research 10, no. 2 (2014): 229. http://dx.doi.org/10.18187/pjsor.v10i2.705.

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Seo, Jung-In, Suk-Bok Kang, and Ho-Yong Kim. "New approach for analysis of progressive Type-II censored data from the Pareto distribution." Communications for Statistical Applications and Methods 25, no. 5 (2018): 569–75. http://dx.doi.org/10.29220/csam.2018.25.5.569.

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Liu, Dongyu, Panpan Xu, and Liu Ren. "TPFlow: Progressive Partition and Multidimensional Pattern Extraction for Large-Scale Spatio-Temporal Data Analysis." IEEE Transactions on Visualization and Computer Graphics 25, no. 1 (2019): 1–11. http://dx.doi.org/10.1109/tvcg.2018.2865018.

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A. Modhesh, A. "Analysis of Progressive First-Failure-Censoring for Non-normal Model Using Competing Risks Data." American Journal of Theoretical and Applied Statistics 4, no. 6 (2015): 610. http://dx.doi.org/10.11648/j.ajtas.20150406.33.

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Tóth, Zsolt, Péter Farkas, and Adrienn Novotni. "Individual tree detection and spatial distribution analysis without reference data." Dimenziók: matematikai közlemények 12 (December 5, 2024): 33–41. https://doi.org/10.20312/dim.2024.04.

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This study processed two 100x100m areas from LiDAR dataset: a forest and a mixed forest-plantation. Progressive Morphological Filtering (PMF) and Local Maximum Filtering (LMF) methods identified 257 trees in the forest and 47 in the mixed area, showing (depending on the method) partly random, partly regular spacing in the forest and clustering in mixed areas. The density assessments and nearest-neighbour evaluations with G statistic, K statistic, Monte Carlo method, and quadrat tests revealed a significant difference in tree distribution, highlighting the effectiveness of these methods for det

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Kim, Yong-Gyun, Sungjoon Kim, Jae Hyeon Park, et al. "Explainable Deep-Learning-Based Gait Analysis of Hip–Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression." Sensors 24, no. 14 (2024): 4504. http://dx.doi.org/10.3390/s24144504.

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Accurate prediction of scoliotic curve progression is crucial for guiding treatment decisions in adolescent idiopathic scoliosis (AIS). Traditional methods of assessing the likelihood of AIS progression are limited by variability and rely on static measurements. This study developed and validated machine learning models for classifying progressive and non-progressive scoliotic curves based on gait analysis using wearable inertial sensors. Gait data from 38 AIS patients were collected using seven inertial measurement unit (IMU) sensors, and hip–knee (HK) cyclograms representing inter-joint coor

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Zuo, Xuanjia, Liang Wang, Huizhong Lin, Sanku Dey, and Li Yan. "Estimation for Weibull Parameters with Generalized Progressive Hybrid Censored Data." Journal of Mathematics 2021 (December 3, 2021): 1–13. http://dx.doi.org/10.1155/2021/5561191.

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In this paper, the interest is in estimating the Weibull products when the available data is obtained via generalized progressive hybrid censoring. The testing scheme conducts products of interest under a more flexible way and allows collecting failure data in efficient and adaptable experimental scenarios than traditional lifetime testing. When the latent lifetime of products follows Weibull distribution, classical and Bayesian inferences are considered for unknown parameters. The existence and uniqueness of maximum likelihood estimates are established, and approximate confidence intervals ar

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