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r script running in the open-source rstudio program version 2024.09.0+375  (RStudio)

 
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    RStudio r script running in the open-source rstudio program version 2024.09.0+375
    R Script Running In The Open Source Rstudio Program Version 2024.09.0+375, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/open-source+script/rstudio+version+1+3+1093/pmc12030427-99-24-30
    Average 90 stars, based on 1 article reviews
    r script running in the open-source rstudio program version 2024.09.0+375 - by Bioz Stars, 2026-10
    90/100 stars

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    other:

    Article Title: Combined genome and transcriptome analysis identifies molecular signatures of aortic disease in patients with Marfan syndrome
    Article Snippet: Gene expression analysis was performed using DESeq2 (v1.38.3) in RStudio (v4.2.1).

    Article Title: Nutritional deficiencies and muscle loss in adults with type 2 diabetes using GLP-1 receptor agonists: A retrospective observational study
    Article Snippet: Statistical analysis was conducted using RStudio 2022.07.1 + 554 and R4.2.1.

    Article Title: Hepatic artery infusion chemotherapy combined with lenvatinib and PD-1 inhibitors in the treatment of intermediate and advanced unresectable hepatocellular carcinoma
    Article Snippet: Statistical analyses were performed using R (RStudio, Inc.; version 4.2.1) and SPSS (IBM Corp.; version 26.0).

    Article Title: Gut Prevotella copri abundance linked to elevated post-exercise inflammation
    Article Snippet: Other statistical analyses were performed in RStudio Version 2023.12.1+402 using R Version 4.4.

    Article Title: Resting-State Network Dynamics in Asthma: Interplay Between Depressive Symptoms and Airway Inflammation
    Article Snippet: Statistical analyses were conducted in CONN or R (version 4.4.0) ( ) with RStudio (version 2024.04.0) ( ).

    Article Title: Outcomes of a 24-month study of patients with HIV with Cryptococcal meningitis on high-dose fluconazole induction in Abidjan, Côte d'Ivoire, between 2012 and 2016
    Article Snippet: Data were entered using Epi Data software version 3.1 and analyzed with R Studio software version 1.043.

    Article Title: Infectious disease risk after the October 2024 flash flood in Valencia, Spain: Disaster evolution, strategic scenario analysis, and extrapolative baseline for a One Health assessment
    Article Snippet: Modelling will be developed with the R Statistical Software 4.1.2 (“R: A language and environment for statistical computing,” www.r-project.org ) and RStudio 2022.02.3.492 (‘RStudio: Integrated development environment for R', http://www.rstudio.com/ ).

    Software:

    Article Title: Novel Analytical Data on Cadmium, Mercury, Lead, Arsenic and Selenium Content in fish fromTanzania and Mozambique: Implications for Food Safety
    Article Snippet: Fish are important for food security and nutrition in many coastal communities; however, fish consumption is also a major source of metal and metalloid exposure to humans.. Data on metal/metalloid content in fish from Tanzania and Mozambique marine waters are limited.. This study analysed the content and assessed the risk of exposure from 17 fish species sampled off the coast of Tanzania and Mozambique by research vessel Dr. Fridtjof Nansen during an ecosystem survey in 2018.



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    Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and <t>the</t> <t>three-dimensional</t> kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of <t>1-SPM</t> to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.
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    Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and the three-dimensional kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of 1-SPM to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.

    Journal: Heliyon

    Article Title: A new method applied for explaining the landing patterns: Interpretability analysis of machine learning

    doi: 10.1016/j.heliyon.2024.e26052

    Figure Lengend Snippet: Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and the three-dimensional kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of 1-SPM to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.

    Article Snippet: For the implementation of SPM, the open-source MATLAB script (paired-samples T-test) of One-Dimensional SPM (SPM 1D) was employed to test the statistical differences, and the significance threshold was set as 0.05 [ , ].

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