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Artículos de revistas sobre el tema "Randomized iterative methods"

Autor: Grafiati

Publicado: 1 de junio de 2024

Última modificación: 31 de julio de 2025

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1

Gower, Robert M., and Peter Richtárik. "Randomized Iterative Methods for Linear Systems." SIAM Journal on Matrix Analysis and Applications 36, no. 4 (2015): 1660–90. http://dx.doi.org/10.1137/15m1025487.

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2

Loizou, Nicolas, and Peter Richtárik. "Convergence Analysis of Inexact Randomized Iterative Methods." SIAM Journal on Scientific Computing 42, no. 6 (2020): A3979—A4016. http://dx.doi.org/10.1137/19m125248x.

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3

Xing, Lili, Wendi Bao, Ying Lv, Zhiwei Guo, and Weiguo Li. "Randomized Block Kaczmarz Methods for Inner Inverses of a Matrix." Mathematics 12, no. 3 (2024): 475. http://dx.doi.org/10.3390/math12030475.

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In this paper, two randomized block Kaczmarz methods to compute inner inverses of any rectangular matrix A are presented. These are iterative methods without matrix multiplications and their convergence is proved. The numerical results show that the proposed methods are more efficient than iterative methods involving matrix multiplications for the high-dimensional matrix.

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4

Zhao, Jing, Xiang Wang, and Jianhua Zhang. "Randomized average block iterative methods for solving factorised linear systems." Filomat 37, no. 14 (2023): 4603–20. http://dx.doi.org/10.2298/fil2314603z.

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Recently, some randomized iterative methods are proposed to solve large-scale factorised linear systems. In this paper, we present two randomized average block iterative methods which still take advantage of the factored form and need not perform the entire matrix. The new methods are pseudoinverse-free and can be implemented for parallel computation. Furthermore, we analyze their convergence behaviors and obtain the exponential convergence rate. Finally, some numerical examples are carried out to show the effectiveness of our new methods.

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5

Song, Hui, Wendi Bao, Lili Xing, and Weiguo Li. "On randomized multiple row-action methods for linear feasibility problems." Networks and Heterogeneous Media 19, no. 4 (2024): 1448–69. https://doi.org/10.3934/nhm.2024062.

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<p>In this paper, for solving linear feasibility problems we propose two randomized methods: a multiple row-action method (RMR) based on partial rows of residual vectors and its generalized method (GRMR) with history information in updating the current update. By introducing a linear combination of the information from the previous and subsequent iterative steps with the relaxation parameter $ \xi $, the GRMR method unifies various RMR-type algorithms. A thorough convergence analysis for the proposed methods is provided. The theoretical results show the theoretical convergence rate of th

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6

Zhang, Yanjun, and Hanyu Li. "Splitting-based randomized iterative methods for solving indefinite least squares problem." Applied Mathematics and Computation 446 (June 2023): 127892. http://dx.doi.org/10.1016/j.amc.2023.127892.

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7

Zheng, Wei, Lili Xing, Wendi Bao, and Weiguo Li. "Kaczmarz-Type Methods for Solving Matrix Equation AXB = C." Axioms 14, no. 5 (2025): 367. https://doi.org/10.3390/axioms14050367.

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This paper proposes a class of randomized Kaczmarz and Gauss–Seidel-type methods for solving the matrix equation AXB=C, where the matrices A and B may be either full-rank or rank deficient and the system may be consistent or inconsistent. These iterative methods offer high computational efficiency and low memory requirements, as they avoid costly matrix–matrix multiplications. We rigorously establish theoretical convergence guarantees, proving that the generated sequences converge to the minimal Frobenius-norm solution (for consistent systems) or the minimal Frobenius-norm least squares soluti

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8

Jensen, Erik, Evan C. Coleman, and Masha Sosonkina. "Implementing Asynchronous Linear Solvers Using Non-Uniform Distributions." Journal of Simulation Engineering 2 (July 31, 2020): 6:1–6:18. https://doi.org/10.5281/zenodo.11114215.

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Asynchronous iterative methods may improve the time-to-solution of their synchronous counterparts on highly parallel computational platforms. This paper considers asynchronous iterative linear system solvers that employ non-uniform randomization and develops a new implementation for such methods. Experiments with a two-dimensional finite-difference discrete Laplacian problem are presented. The new finer grain implementation is compared with an existing, block-based, one and shown to be superior in terms of the convergence speed and accuracy. In general, using non-uniform distributions in selec

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9

Yunak, O., M. Klymash, O. Shpur, and V. Mrak. "MATHEMATICAL MODEL OF FRACTAL STRUCTURES RECOGNITION USING NEURAL NETWORK TECHNOLOGY." Information and communication technologies, electronic engineering 3, no. 1 (2023): 1–9. http://dx.doi.org/10.23939/ictee2023.01.001.

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The article goes about the methods of training a neural network to recognize fractal structures with the rotation of iteration elements by means of an improved randomized system of iteration functions. Parameters of fractal structures are used to calculate complex parameters of physical phenomena. They are an effective tool in scientific works and used to calculate quantitative indicators in technical tasks. The calculation of these parameters is a very difficult mathematical problem. This is caused by the fact that it is very difficult to describe the mathematical model of the fractal image,

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10

Sabelfeld, Karl K. "Randomized Monte Carlo algorithms for matrix iterations and solving large systems of linear equations." Monte Carlo Methods and Applications 28, no. 2 (2022): 125–33. http://dx.doi.org/10.1515/mcma-2022-2114.

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Abstract Randomized scalable vector algorithms for calculation of matrix iterations and solving extremely large linear algebraic equations are developed. Among applications presented in this paper are randomized iterative methods for large linear systems of algebraic equations governed by M-matrices. The crucial idea of the randomized method is that the iterations are performed by sampling random columns only, thus avoiding not only matrix-matrix but also matrix-vector multiplications. The suggested vector randomized methods are highly efficient for solving linear equations of high dimension,

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11

Xing, Lili, Wendi Bao, and Weiguo Li. "On the Convergence of the Randomized Block Kaczmarz Algorithm for Solving a Matrix Equation." Mathematics 11, no. 21 (2023): 4554. http://dx.doi.org/10.3390/math11214554.

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A randomized block Kaczmarz method and a randomized extended block Kaczmarz method are proposed for solving the matrix equation AXB=C, where the matrices A and B may be full-rank or rank-deficient. These methods are iterative methods without matrix multiplication, and are especially suitable for solving large-scale matrix equations. It is theoretically proved that these methods converge to the solution or least-square solution of the matrix equation. The numerical results show that these methods are more efficient than the existing algorithms for high-dimensional matrix equations.

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12

Popkov, Yuri S., Yuri A. Dubnov, and Alexey Yu Popkov. "Reinforcement Procedure for Randomized Machine Learning." Mathematics 11, no. 17 (2023): 3651. http://dx.doi.org/10.3390/math11173651.

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This paper is devoted to problem-oriented reinforcement methods for the numerical implementation of Randomized Machine Learning. We have developed a scheme of the reinforcement procedure based on the agent approach and Bellman’s optimality principle. This procedure ensures strictly monotonic properties of a sequence of local records in the iterative computational procedure of the learning process. The dependences of the dimensions of the neighborhood of the global minimum and the probability of its achievement on the parameters of the algorithm are determined. The convergence of the algorithm

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13

Meurant, Gérard. "A Randomized Q-OR Krylov Subspace Method for Solving Nonsymmetric Linear Systems." Mathematics 13, no. 12 (2025): 1953. https://doi.org/10.3390/math13121953.

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The most popular iterative methods for solving nonsymmetric linear systems are Krylov methods. Recently, an optimal Quasi-ORthogonal (Q-OR) method was introduced, which yields the same residual norms as the Generalized Minimum Residual (GMRES) method, provided GMRES is not stagnating. In this paper, we study how to introduce matrix sketching in this algorithm. It allows us to reduce the dimension of the problem in one of the main steps of the algorithm.

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14

Shcherbakova, Elena M., Sergey A. Matveev, Alexander P. Smirnov, and Eugene E. Tyrtyshnikov. "Study of performance of low-rank nonnegative tensor factorization methods." Russian Journal of Numerical Analysis and Mathematical Modelling 38, no. 4 (2023): 231–39. http://dx.doi.org/10.1515/rnam-2023-0018.

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Abstract In the present paper we compare two different iterative approaches to constructing nonnegative tensor train and Tucker decompositions. The first approach is based on idea of alternating projections and randomized sketching for factorization of tensors with nonnegative elements. This approach can be useful for both TT and Tucker formats. The second approach consists of two stages. At the first stage we find the unconstrained tensor train decomposition for the target array. At the second stage we use this initial approximation in order to fix it within moderate number of operations and

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15

Sergeenko, Anna, and Oleg Granichin. "Sensor network control based on randomized and multi-agent approaches." Cybernetics and Physics, Volume 11, 2022, Number 2 (September 30, 2022): 94–105. http://dx.doi.org/10.35470/2226-4116-2022-11-2-94-105.

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In this paper, a development of randomized and multiagent algorithms is presented. The examples and their advantages are discussed. Different combined algorithms which are applicable for the multi-sensor multitarget tracking problem are shown. These algorithms belong to the class of methods used in derivative-free optimization and has proven efficacy in the problems including significant non-statistical uncertainties. The new algorithm which is an Accelerated consensus-based SPSA algorithm is validated through simulation.The main feature of that algorithm, combining the SPSA techniques, iterat

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16

Fukuda, Tatsuki. "Randomized Kaczmarz Algorithm Applied D’Hondt Method for Extremely Massive MIMO Wireless Communication Systems." WSEAS TRANSACTIONS ON COMPUTER RESEARCH 12 (November 15, 2024): 494–502. http://dx.doi.org/10.37394/232018.2024.12.48.

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Extremely massive MIMO (Multiple-Input Multiple-Output) is a technique to enable the spatial diversity. The systems employ a large number of antennas at the base stations, resulting in high computational complexity in various processes of wireless communications. The precoding process is one of them because the process requires the calculation of matrix inversion. The randomized Kaczmarz algorithm(rKA) is an iterative method to obtain the approximation so the computational time of precoding can be decreased. Some improvements of rKA were proposed so far, the iteration number required to obtain

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17

Bao, Rong, Yongdong Li, Hongguang Wang, and Chunliang Liu. "A Multi-Constrained Optimization Method for THz Backward Wave Oscillators." Applied Sciences 12, no. 20 (2022): 10583. http://dx.doi.org/10.3390/app122010583.

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The current design period for various backward wave oscillators (BWOs) is still at least several months. How to find the best structure parameters with an efficient and stable optimization method is a problem facing researchers in both scientific research and engineering work. In this paper, a non-randomized iterative optimization method is proposed. It applies orthogonal design methods to find local solutions that can provide optimal ‘gradient direction’ for several successive next iteration steps. An evaluation function is designed to distinguish the better ones from the local solutions in t

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18

Jia, Cui, and Zhuoxu Cui. "Stagewise Accelerated Stochastic Gradient Methods for Nonconvex Optimization." Mathematics 12, no. 11 (2024): 1664. http://dx.doi.org/10.3390/math12111664.

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For large-scale optimization that covers a wide range of optimization problems encountered frequently in machine learning and deep neural networks, stochastic optimization has become one of the most used methods thanks to its low computational complexity. In machine learning and deep learning problems, nonconvex problems are common, while convex problems are rare. How to find the global minimum for nonconvex optimization and reduce the computational complexity are challenges. Inspired by the phenomenon that the stagewise stepsize tuning strategy can empirically improve the convergence speed in

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19

Ying, Songpeng. "Serveless-based High-Dimensional Matrix Operations and Their Financial Applications." Applied and Computational Engineering 158, no. 1 (2025): 11–16. https://doi.org/10.54254/2755-2721/2025.tj23320.

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This paper systematically analyzes multivariate methods for high-dimensional matrix computation and their optimization strategies for applications in finance. At the level of high-dimensional computation, it focuses on the technical characteristics of direct methods, iterative methods , and randomized algorithms , which reveal their efficiency gains in financial derivatives pricing, risk matrix modeling, and other scenarios. For serverless architecture, the study focuses on its core advantages of elastic scaling and on-demand billing, through parallel task slicing and cost optimization, while

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20

Hurley, James. "Meta-analysis of Clinical Studies of Diagnostic Tests: Developments in How the Receiver Operating Characteristic “Works”." Archives of Pathology & Laboratory Medicine 135, no. 12 (2011): 1585–90. http://dx.doi.org/10.5858/arpa.2011-0016-so.

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Meta-analytic summaries are needed on clinical studies of diagnostic tests. Meta-analyses on clinical studies of diagnostic tests commonly use the receiver operating characteristic method, which differs conceptually and computationally from the more widely known meta-analytic methods applicable in other contexts, such as in studies of randomized controlled trials. Important conceptual differences for clinical studies of diagnostic tests versus randomized controlled trials are that the study subpopulations are not defined by random allocation and the test threshold typically varies across studi

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21

Mullane, Sarah L., Dana R. Epstein, and Matthew P. Buman. "The “House of Quality for Behavioral Science”—a user-centered tool to design behavioral interventions." Translational Behavioral Medicine 9, no. 4 (2018): 810–18. http://dx.doi.org/10.1093/tbm/iby084.

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Abstract Within the behavioral field, a plethora of conceptual frameworks and tools have been developed to improve transition from efficacy to effectiveness trials; however, they are limited in their ability to support new, iterative intervention design decision-making methodologies beyond traditional randomized controlled trial design. Emerging theories suggest that researchers should employ engineering based user-centered design (UCD) methods to support more iterative intervention design decision-making in the behavioral field. We present, an adaptation of a UCD tool used in the engineering

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22

Armin, Julie S., Uma Nair, Peter Giacobbi, Gayle Povis, Yessenya Barraza, and Judith S. Gordon. "Developing a Guided Imagery Telephone-Based Tobacco Cessation Program for a Randomized Controlled Trial." Tobacco Use Insights 13 (January 2020): 1179173X2094926. http://dx.doi.org/10.1177/1179173x20949267.

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Background/Aims: Guided imagery is an evidence-based, multi-sensory, cognitive process that can be used to increase motivation and achieve a desired behavior. Quitlines are effective, standard care approaches for tobacco cessation; however, utilization of quitlines is low. Using guided imagery-based interventions for smoking cessation may appeal to smokers who do not utilize traditional quitline services. This paper reports the development of program materials for a randomized controlled feasibility trial of a guided imagery-based smoking cessation intervention. The objective of the formative

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23

Lowe, Cabella, Harry Hanuman Sing, Mitchell Browne, Meshari F. Alwashmi, William Marsh, and Dylan Morrissey. "Usability Testing of a Digital Assessment Routing Tool: Protocol for an Iterative Convergent Mixed Methods Study." JMIR Research Protocols 10, no. 5 (2021): e27205. http://dx.doi.org/10.2196/27205.

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Background Musculoskeletal conditions account for 16% of global disability, resulting in a negative effect on millions of patients and an increasing burden on health care utilization. Digital technologies that improve health care outcomes and efficiency are considered a priority; however, innovations are often inadequately developed and poorly adopted. Further, they are rarely tested with sufficient rigor in clinical trials—the gold standard for clinical proof of efficacy. We have developed a new musculoskeletal Digital Assessment Routing Tool (DART) that allows users to self-assess and be dir

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24

АКСЮК, И. А., А. Е. КИРЕЕВА, К. К. САБЕЛЬФЕЛЬД та Д. Д. СМИРНОВ. "АЛГОРИТМЫ СТОХАСТИЧЕСКОГО МОДЕЛИРОВАНИЯ ДЛЯ ИТЕРАЦИОННОГО РЕШЕНИЯ УРАВНЕНИЯ ЛАМЕ". Сибирский журнал вычислительной математики 26, № 4 (2023): 357–77. http://dx.doi.org/10.15372/sjnm20230402.

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В статье построены итерационные алгоритмы стохастического моделирования для решения системы уравнений Ламе, описывающей смещения изотропного упругого тела. Предложено три различных стохастических метода. Первый основан на глобальном алгоритме блуждания по сферам для вычисления решения и производных для анизотропного уравнения диффузии. Он является бессеточным и не требует большой оперативной памяти. Второй метод основан на рандомизированном алгоритме для решения больших систем линейных уравнений и требует введения сеток. Третий метод также является сеточным, он использует алгоритм случайного б

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25

Ray, Abhishek, Mario Ventresca, and Karthik Kannan. "A Graph-Based Ant Algorithm for the Winner Determination Problem in Combinatorial Auctions." Information Systems Research 32, no. 4 (2021): 1099–114. http://dx.doi.org/10.1287/isre.2021.1031.

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Iterative combinatorial auctions are known to resolve bidder preference elicitation problems. However, winner determination is a known key bottleneck that has prevented widespread adoption of such auctions, and adding a time-bound to winner determination further complicates the mechanism. As a result, heuristic-based methods have enjoyed an increase in applicability. We add to the growing body of work in heuristic-based winner determination by proposing an ant colony metaheuristic–based anytime algorithm that produces optimal or near-optimal winner determination results within specified time.

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Bruce, Beau B., Robert El-Kareh, John W. Ely, et al. "Methodologies for evaluating strategies to reduce diagnostic error: report from the research summit at the 7th International Diagnostic Error in Medicine Conference." Diagnosis 3, no. 1 (2016): 1–7. http://dx.doi.org/10.1515/dx-2016-0002.

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AbstractIn this article we review current evidence on strategies to evaluate diagnostic error solutions, discuss the methodological challenges that exist in investigating the value of these strategies in patient care, and provide recommendations for methods that can be applied in investigating potential solutions to diagnostic errors. These recommendations were developed iteratively by the authors based upon initial discussions held during the Research Summit of the 7th Annual Diagnostic Error in Medicine Conference in September 2014. The recommendations include the following elements for desi

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27

Willcox, Jane C., Daniel Chai, Lawrence J. Beilin, et al. "Evaluating Engagement in a Digital and Dietetic Intervention Promoting Healthy Weight Gain in Pregnancy: Mixed Methods Study." Journal of Medical Internet Research 22, no. 6 (2020): e17845. http://dx.doi.org/10.2196/17845.

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Background Early excess and inadequate gestational weight gain (GWG) have been associated with negative outcomes for mother and child. The use of digital media to deliver pregnancy lifestyle interventions is increasing, but there is little data on participant engagement. The Pregnancy Lifestyle Activity and Nutrition (PLAN) intervention pilot study was an electronic health and dietetic-delivered intervention program promoting healthy GWG in early pregnancy. Objective This study aims to explore the interactions of participants with the program and to assess its acceptability. Methods This study

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28

Davtyan, Aram, Sepehr Sameni, Llukman Cerkezi, Givi Meishvili, Adam Bielski, and Paolo Favaro. "KOALA: A Kalman Optimization Algorithm with Loss Adaptivity." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (2022): 6471–79. http://dx.doi.org/10.1609/aaai.v36i6.20599.

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Optimization is often cast as a deterministic problem, where the solution is found through some iterative procedure such as gradient descent. However, when training neural networks the loss function changes over (iteration) time due to the randomized selection of a subset of the samples. This randomization turns the optimization problem into a stochastic one. We propose to consider the loss as a noisy observation with respect to some reference optimum. This interpretation of the loss allows us to adopt Kalman filtering as an optimizer, as its recursive formulation is designed to estimate unkno

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29

Burke, Holly M., Catherine Packer, Akuzike Zingani, et al. "Testing a counseling message for increasing uptake of self-injectable contraception in southern Malawi: A mixed-methods, clustered randomized controlled study." PLOS ONE 17, no. 10 (2022): e0275986. http://dx.doi.org/10.1371/journal.pone.0275986.

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Objective While self-injection of subcutaneous depot medroxyprogesterone acetate (DMPA-SC) has well-documented benefits, uptake may be improved by addressing client concerns such as fear of self-injury and low self-efficacy. However, current training materials for family planning providers do not address these concerns. We used an iterative process with family planning providers and clients, male community leaders and partners, and stakeholders in Malawi to develop a counseling message addressing user-centered concerns about self-injection. We report on our testing of the effectiveness of this

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30

Chen, Jinghui, Yu Cheng, Zhe Gan, Quanquan Gu, and Jingjing Liu. "Efficient Robust Training via Backward Smoothing." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (2022): 6222–30. http://dx.doi.org/10.1609/aaai.v36i6.20571.

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Adversarial training is so far the most effective strategy in defending against adversarial examples. However, it suffers from high computational costs due to the iterative adversarial attacks in each training step. Recent studies show that it is possible to achieve fast Adversarial Training by performing a single-step attack with random initialization. However, such an approach still lags behind state-of-the-art adversarial training algorithms on both stability and model robustness. In this work, we develop a new understanding towards Fast Adversarial Training, by viewing random initializatio

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31

Brint, Steve, Michael Jacewicz, Marika Kiessling, Jody Tanabe, and William Pulsinelli. "Focal Brain Ischemia in the Rat: Methods for Reproducible Neocortical Infarction Using Tandem Occlusion of the Distal Middle Cerebral and Ipsilateral Common Carotid Arteries." Journal of Cerebral Blood Flow & Metabolism 8, no. 4 (1988): 474–85. http://dx.doi.org/10.1038/jcbfm.1988.88.

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This article describes a 3-year experience with focal neocortical ischemia in three rat strains. Multiple groups of adult Wistar (n = 50), Fisher 344 (n = 31), and spontaneously hypertensive (n = 72) rats were subjected to permanent occlusion of the distal middle cerebral (MCA) and ipsilateral common carotid arteries (CCA). Twenty-four hours later the animals were killed, and frozen brain sections were stained with hematoxylin and eosin to demarcate infarcted tissue. The infarct volume for each section was quantified with an image analyzer, and the total infarct volume was calculated with an i

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32

de la Torre, Angel, Joaquin T. Valderrama, Jose C. Segura, Isaac M. Alvarez, and Jesus Garcia-Miranda. "Subspace-constrained deconvolution of auditory evoked potentials." Journal of the Acoustical Society of America 151, no. 6 (2022): 3745–57. http://dx.doi.org/10.1121/10.0011423.

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Auditory evoked potentials can be estimated by synchronous averaging when the responses to the individual stimuli are not overlapped. However, when the response duration exceeds the inter-stimulus interval, a deconvolution procedure is necessary to obtain the transient response. The iterative randomized stimulation and averaging and the equivalent randomized stimulation with least squares deconvolution have been proven to be flexible and efficient methods for deconvolving the evoked potentials, with minimum restrictions in the design of stimulation sequences. Recently, a latency-dependent filt

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33

Gautam, Mahesh, Aziz Ullah, and Manish Raj Pathak. "Low Dose Computed Tomography in Diagnosis of Ureteric Calculus in Obese Patients." Journal of Nobel Medical College 9, no. 1 (2020): 27–31. http://dx.doi.org/10.3126/jonmc.v9i1.29464.

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Background: Standard dose computed tomography is standard imaging modality in diagnosis of urolithiasis. The introduction of low dose techniques results in decrease radiation dose without significant change in image quality. However, the image quality of low dose computed tomography is affected by skin fold thickness and subcutaneous abdominal adipose tissue. The aim of this study to evaluate stone location, size, and density using low dose computed tomography compared with standard dose computed tomography in obese population. Material and Methods: This non-randomized non-inferiority tr

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Koch, Sabine, Kim M. Unertl, Christoph U. Lehmann, and Kevin R. Dufendach. "A Randomized Trial Comparing Classical Participatory Design to VandAID, an Interactive CrowdSourcing Platform to Facilitate User-centered Design." Methods of Information in Medicine 56, no. 05 (2017): 344–49. http://dx.doi.org/10.3414/me16-01-0098.

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Summary Background: Early involvement of stakeholders in the design of medical software is particularly important due to the need to incorporate complex knowledge and actions associated with clinical work. Standard user-centered design methods include focus groups and participatory design sessions with individual stakeholders, which generally limit user involvement to a small number of individuals due to the significant time investments from designers and end users. Objectives: The goal of this project was to reduce the effort for end users to participate in co-design of a software user interf

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35

Abrams, Keith R., Nicholas Latimer, Mayur Amonkar, Ceilidh Stapelkamp, and Michelle Casey. "Adjusting for treatment crossover in the METRIC metastatic melanoma (MM) trial for trametinib: Preliminary analysis." Journal of Clinical Oncology 31, no. 15_suppl (2013): 9040. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.9040.

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9040 Background: In METRIC, a randomized phase III study, trametinib significantly improved PFS (hazard ratio [HR]=0.44 [95% CI 0.31–0.64; p<0.001]) vs chemotherapy (chemo) in patients (pts) with BRAF V600E+ MM and no brain metastases. Median overall survival (OS), a secondary endpoint, has not yet been reached. OS results are likely to underestimate the effect of trametinib as pts progressing on chemo could cross over to experimental treatment (trt). This analysis attempts to adjust for confounding effects of trt crossover on OS in the overall population and first line (1L) subgroup using

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Salehi, Bahram, Sina Jarahizadeh, and Amin Sarafraz. "An Improved RANSAC Outlier Rejection Method for UAV-Derived Point Cloud." Remote Sensing 14, no. 19 (2022): 4917. http://dx.doi.org/10.3390/rs14194917.

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A common problem with matching algorithms, in photogrammetry and computer vision, is the imperfection of finding all correct corresponding points, so-called inliers, and, thus, resulting in incorrect or mismatched points, so-called outliers. Many algorithms, including the well-known randomized random sample consensus (RANSAC)-based matching, have been developed focusing on the reduction of outliers. RANSAC-based methods, however, have limitations such as increased false positive rates of outliers, and, consequently resulting in fewer inliers, an unnecessary high number of iterations, and high

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Agarwal, Arnav, John Basmaji, Shannon M. Fernando, et al. "Administration of Parenteral Vitamin C in Patients With Severe Infection: Protocol for a Systematic Review and Meta-analysis." JMIR Research Protocols 11, no. 1 (2022): e33989. http://dx.doi.org/10.2196/33989.

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Background Severe infections are characterized by inflammation and oxidative damage. Ascorbic acid (vitamin C) administration may attenuate oxidative damage and, in turn, reduce vascular endothelial injury in pulmonary and systemic vasculature. Objective We aim to describe a protocol for a living systematic review that will evaluate the effectiveness and safety of parenteral vitamin C administration in adults with severe infections, including those with COVID-19. Methods We searched Ovid MEDLINE, Embase, CINAHL, the Centers for Disease Control and Prevention COVID-19 database, Cochrane Central

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Riddle, Sarah W., Susan N. Sherman, Margo J. Moore, et al. "A Qualitative Study of Increased Pediatric Reutilization After a Postdischarge Home Nurse Visit." Journal of Hospital Medicine 15, no. 9 (2020): 518–25. http://dx.doi.org/10.12788/jhm.3370.

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BACKGROUND: The Hospital to Home Outcomes (H2O) trial was a 2-arm, randomized controlled trial that assessed the effects of a nurse home visit after a pediatric hospital discharge. Children randomized to the intervention had higher 30-day postdischarge reutilization rates compared with those with standard discharge. We sought to understand perspectives on why postdischarge home nurse visits resulted in higher reutilization rates and to elicit suggestions on how to improve future interventions. METHODS: We sought qualitative input using focus groups and interviews from stakeholder groups: paren

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Krishnamurti, Lakshmanan, Diana Ross, Cynthia Sinha, et al. "Comparative Effectiveness of a Web-Based Patient Decision Aid for Therapeutic Options for Sickle Cell Disease: Randomized Controlled Trial." Journal of Medical Internet Research 21, no. 12 (2019): e14462. http://dx.doi.org/10.2196/14462.

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Background Hydroxyurea, chronic blood transfusions, and bone marrow transplantation are efficacious, disease-modifying therapies for sickle cell disease but involve complex risk-benefit trade-offs and decisional dilemma compounded by the lack of comparative studies. A patient decision aid can inform patients about their treatment options, the associated risks and benefits, help them clarify their values, and allow them to participate in medical decision making. Objective The objective of this study was to develop a literacy-sensitive Web-based patient decision aid based on the Ottawa decision

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Sun, Guangling, Yuying Su, Chuan Qin, Wenbo Xu, Xiaofeng Lu, and Andrzej Ceglowski. "Complete Defense Framework to Protect Deep Neural Networks against Adversarial Examples." Mathematical Problems in Engineering 2020 (May 11, 2020): 1–17. http://dx.doi.org/10.1155/2020/8319249.

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Although Deep Neural Networks (DNNs) have achieved great success on various applications, investigations have increasingly shown DNNs to be highly vulnerable when adversarial examples are used as input. Here, we present a comprehensive defense framework to protect DNNs against adversarial examples. First, we present statistical and minor alteration detectors to filter out adversarial examples contaminated by noticeable and unnoticeable perturbations, respectively. Then, we ensemble the detectors, a deep Residual Generative Network (ResGN), and an adversarially trained targeted network, to cons

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Alfonsi, Jeffrey E., Elizabeth E. Y. Choi, Taha Arshad, et al. "Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial." JMIR mHealth and uHealth 8, no. 10 (2020): e22074. http://dx.doi.org/10.2196/22074.

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Background Carbohydrate counting is an important component of diabetes management, but it is challenging, often performed inaccurately, and can be a barrier to optimal diabetes management. iSpy is a novel mobile app that leverages machine learning to allow food identification through images and that was designed to assist youth with type 1 diabetes in counting carbohydrates. Objective Our objective was to test the app's usability and potential impact on carbohydrate counting accuracy. Methods Iterative usability testing (3 cycles) was conducted involving a total of 16 individuals aged 8.5-17.0

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Abbott, Laurie, Jessica De Leon, and Lucinda Graven. "Impact of a Web-Based Lifestyle Medicine Intervention: A Qualitative Study Among Rural Participants." Nursing Reports 15, no. 7 (2025): 227. https://doi.org/10.3390/nursrep15070227.

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Background: Chronic diseases negatively impact health outcomes and are attributed to elevated morbidity and mortality throughout the world. Rural populations are disproportionately affected by chronic diseases and have limited access to health programs and resources. The purpose of this qualitative study was to explore the cognitive impact that a web-based lifestyle medicine intervention had on participants recruited from rural community settings in the southeastern United States. This qualitative study was the second phase of a mixed methods design, which used a randomized controlled trial to

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Samuel, P., J. Park, F. Muckle, et al. "P036: A comprehensive quality improvement initiative to prevent falls in the emergency department." CJEM 19, S1 (2017): S90. http://dx.doi.org/10.1017/cem.2017.238.

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Introduction: Patients from all population groups visit the emergency department (ED), with increasing visits by elderly patients. Patient falls in the ED are a significant safety concern, and they can lead to serious injuries and worse outcomes. Toronto Western Hospital’s ED Quality Improvement (QI) team identified as a problem our assessment and management of patients at risk for falls. The aim of this project was to develop a comprehensive and standardized approach to patients at risk of falls in the ED, including implementing timely interventions for fall prevention. Methods: A literature

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Young, E., R. Aiyadurai, U. Cellupica, et al. "The Generalizability of the Paediatric Developmental Passport: A Multi-Site Randomized Controlled Trial." Paediatrics & Child Health 21, Supplement_5 (2016): e67a-e67a. http://dx.doi.org/10.1093/pch/21.supp5.e67a.

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Abstract BACKGROUND: The Pediatric Developmental Passport (passport) is an innovative tracking tool for families of children with autism spectrum disorder (ASD). It provides a mechanism for clearly communicating appropriate regional developmental services, an opportunity track progress in accessing these developmental services and a valuable summary of the developmental care received by that child for pediatrician. A qualitative study with parents and health professionals (developmental pediatricians, developmental nurses, pediatricians) lead to the design and iterative review of the passport.

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Nardell, Maria F., Siyaxolisa Sindelo, Elzette Rousseau, et al. "Development of “Yima Nkqo,” a community-based, peer group intervention to support treatment initiation for young adults with HIV in South Africa." PLOS ONE 18, no. 6 (2023): e0280895. http://dx.doi.org/10.1371/journal.pone.0280895.

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Aims Half of young adults diagnosed with HIV in South Africa start antiretroviral therapy (ART). We developed and field tested a facilitator-guided peer support group called Yima Nkqo (“Standing Tall” in isiXhosa) to promote treatment initiation for young adults newly diagnosed with HIV in communities around Cape Town. Methods Following an adapted version of the UK Medical Research Council’s framework for developing complex interventions, we 1) identified evidence on previous interventions to improve ART uptake in sub-Saharan Africa; 2) collected and analyzed qualitative data on the acceptabil

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Bhat, Amritha, B. Ramakrishna Goud, Bharat Kalidindi, et al. "Mobile Mental Health in Women’s Community-Based Organizations: Protocol for a Pilot Randomized Controlled Trial." JMIR Research Protocols 12 (February 8, 2023): e42919. http://dx.doi.org/10.2196/42919.

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Background Of every 10 women in rural India, 1 suffers from a common mental disorder such as depression, and untreated depression is associated with significant morbidity and mortality. Several factors lead to a large treatment gap, specifically for women in rural India, including stigma, lack of provider mental health workforce, and travel times. There is an urgent need to improve the rates of detection and treatment of depression among women in rural India without overburdening the scarce mental health resources. Objective We propose to develop, test, and deploy a mental health app, MITHRA (

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Ojagbemi, Akin, Roberto Mediavilla, Stephanie Daley, et al. "Home-based depression care for older people delivered by lay providers in Nigeria: protocol for a proof-of-concept cluster randomised controlled trial using an age adapted electronic mental health gap action programme intervention guide app for mobile devices." Wellcome Open Research 9 (July 2, 2024): 352. http://dx.doi.org/10.12688/wellcomeopenres.22445.1.

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Background We conducted iterative adaptation of the generic e-version (2.0) of the WHO Mental Health Gap Action Programme Intervention Guide (emhGAP-IG) to overcome the challenges in detection and home-based management of depression in older people by frontline non-specialist Primary Health Care (PHC) workers. Objectives In this study, we will assess early implementation outcomes (feasibility, appropriateness, and acceptability) and evaluate parameters and procedures to inform a larger trial of the age adapted emhGAP-IG (emhGAP-Age) for home-based management of depression in older people. Meth

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Debeuf, Ruben, Reinhard Claeys, Margo Berlanger, et al. "Insights on the User Experience and Feasibility of an Electromyography-Driven Exergame Combined With Blood Flow Restriction for Strength Training in Hospitalized Older Adults: Mixed Methods Randomized Controlled Feasibility Study." JMIR Serious Games 13 (June 10, 2025): e69400-e69400. https://doi.org/10.2196/69400.

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Abstract Background Hospitalized older adults often spend prolonged periods of time bedridden, leading to decreased muscle strength and function. To tackle this, rehabilitation aims to keep patients active and train affected muscles. Exergames have proven to be effective in the rehabilitation of different patient populations and offer a motivating solution to combat inactivity associated with hospitalization. Furthermore, blood flow restriction (BFR) is effective in therapy for weakened patients, so combining BFR and exergames might be promising. Objective As part of an iterative process of us

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Vallejo-Torres, Laura, Lotte Steuten, Bonny Parkinson, Alan J. Girling, and Martin J. Buxton. "Integrating Health Economics Into the Product Development Cycle." Medical Decision Making 31, no. 4 (2010): 596–610. http://dx.doi.org/10.1177/0272989x10388041.

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Background. The probability of reimbursement is a key factor in determining whether to proceed with or abandon a product during its development. The purpose of this article is to illustrate how the methods of iterative Bayesian economic evaluation proposed in the literature can be incorporated into the development process of new medical devices, adapting them to face the relative scarcity of data and time that characterizes the process. Methods. A 3-stage economic evaluation was applied: an early phase in which simple methods allow for a quick prioritization of competing products; a mid-stage

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O’Connor, Ashley, Amy Ladebue, Jamie Peterson, et al. "Creating and testing regulatory focus messages to enhance medication adherence." Chronic Illness 15, no. 2 (2018): 124–37. http://dx.doi.org/10.1177/1742395317753882.

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Objectives Strategies were explored to improve patient adherence to cardioprotective medications by borrowing from a motivational framework used in psychology, regulatory focus theory. The current study is part of a larger randomized control trial and was aimed at understanding what written educational messages, based on patients’ regulatory focus tendency, resonated with each individual as a potential reminder to take medications. This study was also aimed at understanding why messages resonated with the patients. Methods Twenty veterans were tested for regulatory fitand presented with messag

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