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  1. 5541
    “…Kinematic data were extracted from videos post-hoc using the Python-based computer vision suite DeepLabCut. Both manual and automated (80.00% accuracy) approaches were used to extract kinematic episodes from threshold derived kinematic fluctuations. …”
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    Automatic extraction of upper-limb kinematic activity using deep learning-based markerless tracking during deep brain stimulation implantation for Parkinson’s disease: A proof of concept study
  2. 5542
    “…Then we select 10 low-cost airlines and 10 full-service airlines, respectively, according to the number of reviews sorted by the TripAdvisor website, and use crawling techniques to obtain 10,485 reviews related to COVID-19 safety of the above companies from December 2019 to date, and conduct safety perception sentiment analysis based on Python’s Textblob library. Finally, to avoid data overdispersion, the model is empirically analyzed by negative binomial regression using R software. …”
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    Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures
  3. 5543
    “…Publication information, citations, authors, commonly used terms, and affiliated institutions and countries were analyzed by VOSviewer and Python. RESULTS: A total of 553 articles were included for analysis. …”
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    Trends in Anterior Cruciate Ligament Repair: A Bibliometric and Visualized Analysis
  4. 5544
    “…In order to accurate assessment of particulate matter concentration, a new model was proposed to resample cement plant time series data using Pandas in Python. The effect of meteorological parameters including wind speed, relative humidity, air temperature and rainfall on the particulate matter concentration was investigated through statistical analysis. …”
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    On the predictability of short-lived particulate matter around a cement plant in Kerman, Iran: machine learning analysis
  5. 5545
    “…METHODS: We collected 1289 relevant tweets using the Twint application in Python from January 1 to January 31, 2022. Thematic analysis was used to analyze the data. …”
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    Examining the Twitter Discourse on Dementia During Alzheimer’s Awareness Month in Canada: Infodemiology Study
  6. 5546
    “…Statistical Package for Social Sciences (SPSS) 26.0 and Python 3.9 were used for statistical analysis and visualization, and a p-value of less than 0.05 was considered statistically significant. …”
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    Comparison of Imaging Severity Between Vaccinated and Unvaccinated COVID-19 Patients: Perspective of an Indian District
  7. 5547
    “…Datasets processing, bioinformatics analyses, and visualizations were performed with the packages of Python and R. Cell proliferations were demonstrated via CCK8 assays and colony formation assays, and in vivo xenograft experiments. …”
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    The tRNA-Cys-GCA Derived tsRNAs Suppress Tumor Progression of Gliomas via Regulating VAV2
  8. 5548
    “…METHODS: We collected comments using Python-based web-scraping tools from the New York Times, YouTube, Twitter, and Reddit. …”
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    Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study
  9. 5549
    “…Methods: We analyzed AS swept-source (SS)-OCT (CASIA 2) images of 31 patients (51 eyes) with uveitis using image analysis software (Python). An automated algorithm was developed to detect cellular spots corresponding to hyper-reflective spots in the AC, and the correlation with Standardization of Uveitis Nomenclature (SUN) grading AC cells score was evaluated. …”
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    Automated Quantitative Analysis of Anterior Segment Inflammation Using Swept-Source Anterior Segment Optical Coherence Tomography: A Pilot Study
  10. 5550
    por Şen, Şamil
    Publicado 2022
    “…A dataset consisting of 331 samples from 19 wells of various locations of the world-class organic-rich shales of the Niobrara, Eagle Ford, Barnett, Haynesville, Woodford, Vaca Muerta and Dadaş has been used to determination of a DL model for S1 volumes prediction using Python 3 programing environment with Tensorflow and Keras open-source libraries. …”
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    Prediction of fluid oil and gas volumes of shales with a deep learning model and its application to the Bakken and Marcellus shales
  11. 5551
    “…CONCLUSIONS: We packaged all 4 models as a Python-based deep learning classification tool called TULIP (TUmor CLassIfication Predictor) for performing quality control on primary tumor samples and characterizing cancer samples of unknown tumor type. …”
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    TULIP: An RNA-seq-based Primary Tumor Type Prediction Tool Using Convolutional Neural Networks
  12. 5552
    “…This approach leverages structured covariation across individual experiences and is available in Neighbors, an open-source Python toolbox. We validate our approach across three different experimental contexts by recovering dense individual ratings using only a small subset of the original data. …”
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    Recovering Individual Emotional States from Sparse Ratings Using Collaborative Filtering
  13. 5553
    “…Survey responses were analyzed using Python for statistical analysis. RESULTS: Sixty-five respondents completed the survey. …”
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    1013. Outpatient parenteral antimicrobial therapy (OPAT)-related peripheral eosinophilia as a predictor of hypersensitivity reactions.
  14. 5554
    “…Simulations are conducted in Python 3.4 to model the propagation of COVID-19 between Feb, 6 to Mar 20, 2020 in China. …”
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    A new method for spatio-temporal transmission prediction of COVID-19
  15. 5555
    “…All the models were trained using the open-source Python library scikit-survival version 0.16.0. Shapley additive explanations method was used to help clinicians better understand the obtained results. …”
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    Feasibility of machine learning-based modeling and prediction using multiple centers data to assess intrahepatic cholangiocarcinoma outcomes
  16. 5556
    “…Automatic data processing and analysis are now managed via Dahu, an online server with upstream data reduction, data scaling and azimuthal integration built around PyFAI (Python Fast Azimuthal Integration), and data analysis performed using the open source FreeSAS. …”
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    BioSAXS at European Synchrotron Radiation Facility – Extremely Brilliant Source: BM29 with an upgraded source, detector, robot, sample environment, data collection and analysis software
  17. 5557
    “…We also provide an accommodating C and Python based package that implements RCFGL.…”
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    RCFGL: Rapid Condition adaptive Fused Graphical Lasso and application to modeling brain region co-expression networks
  18. 5558
    “…Population characteristics were obtained via PLINK, SVS, Admixture, and Treemix software, within-breed network was analysed with python networkx 2.3 library. Daily weight gain of Hungarian Merino was standardised to 60 days and was collected from the database of the Association of Hungarian Sheep and Goat Breeders. …”
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    Position of Hungarian Merino among other Merinos, within-breed genetic similarity network and markers associated with daily weight gain
  19. 5559
    “…We present an open-source software called similarity downselection (SDS), written in Python and freely available on GitHub. SDS implements a heuristic algorithm for quickly finding the approximate set(s) of the n most dissimilar items. …”
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    Similarity Downselection: Finding the n Most Dissimilar Molecular Conformers for Reference-Free Metabolomics
  20. 5560
    “…Five machine learning methods (KNN algorithm, logistic regression algorithm, random forest algorithm, support vector machine, and XGBoost algorithm) were compared to evaluate their performances in prediction accuracy. R 3.6.3 and Python 3.12 were used in data analysis. RESULTS: The statistical variables for which p< 0.05 was obtained were BMI, pulse, Na, Cl, AKP. …”
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    Implementation of five machine learning methods to predict the 52-week blood glucose level in patients with type 2 diabetes
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