“…We implemented logistic regression (LR), extreme gradient boosting (XGBoost), gradient boosting machines, adaptive boosting, and random forest classifiers in Python and trained these models using 64 binary, continuous, and discrete variables to predict the occurrence of at least one major postoperative complication or readmission following primary rTSA. …”
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“…We implemented the conceptual framework in two Python packages, calibr8 and murefi, with which we demonstrate how to make uncertainty quantification for various calibration tasks more accessible. …”
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“…All calculations were done using CatBoostClassifier in Python. RESULTS: There were 127,018 patients that served as the basis for these analyses. …”
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“…CONCLUSIONS: We bundled the algorithm into the open-source Python package and command line program Hydride. Since usually no additional parametrization is necessary for the problem at hand, the software works out-of-box for a wide range of molecular systems usually within a few seconds of computation time. …”
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“…Conventional and persistence-based evaluation is implemented in Python code and available as open access supplement. …”
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“…From a computing perspective, XSim Version 2 is implemented in Julia, which is a computer language that retains the readability of scripting languages (e.g. R and Python) without sacrificing much computational speed compared to compiled languages (e.g. …”
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“…For the execution of the selection of variables and the creation and validation of predictive models, two tools were used: the scikit-learn library for Python, and the Weka application. The logistic regression model provided a maximum AUD prediction accuracy of 85.07%. …”
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“…RESULTS: Here, we present a tutorial to our Python-based Blender add-on—BlenderPhotonics—to interface with Iso2Mesh and MMC, which allows users to create, configure and refine complex simulation domains and run hardware-accelerated 3D light simulations with only a few clicks. …”
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“…The model was built and simulated using the freely available Python package pymdp. The proposed active inference model can reproduce the formation of echo-chambers over social networks, and gives us insight into the cognitive processes that lead to this phenomenon.…”
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“…AVAILABILITY AND IMPLEMENTATION: The inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/). …”
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“…We analyze real-time data using a time series model in Python, and RMSE and MAPE evaluate cross-validation results. …”
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“…For this work, we collected the dataset from open-source data repository and then pre-process each X-ray images from each category such as covid X-ray images and non-covid X-ray images using various techniques such as filtering, edge detection, segmentation, etc., and then the pre-processed X-ray images are trained using CNN-Resnet18 network. Using PyTorch python package, the resnet-18 network layer is created which gives more accuracy than any other algorithm. …”
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“…The proposed model Boruta with SVM and various popular ML models are implemented using Python and various performance measuring parameters, i.e., accuracy, precision, F1–Score, and recall. …”
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“…The CFVisual package was implemented in Python and is freely available from https://github.com/ChenHuilong1223/CFVisual/. …”
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“…AVAILABILITY AND IMPLEMENTATION: A Python implementation for Boost-RS is provided at https://github.com/HassounLab/Boost-RS. …”
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“…PANDORA is a modularized and user-configurable python package with easy installation. We envision PANDORA to fuel deep learning algorithms with large-scale high-quality 3D models to tackle long-standing immunology challenges.…”
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“…Further visualization, analysis and investigation will be performed using Smart PLS, Python or R language. Conclusions: The study aims to provide context for smartphone and software companies to develop technologies that could facilitate learner motivation and engagement during the post-pandemic state.…”
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“…The original source code in C/C++ was carefully refactored to mitigate the lack of replicability; moreover, it was re-implemented to other programming languages/software (XPP/XPPAUT, Python and Matlab) and executed under two operating systems (Windows and Linux). …”
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“…This was accomplished through the use of Anaconda (Python). To build a strong ensemble learner by integrating weak learners, adaptive boosting, random forest (RF), and ensemble learner bagging were employed. …”
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“…MATERIALS AND METHODS: Our concept extraction Python package, MicrobEx, is built upon a rule-based natural language processing algorithm and was developed using microbiology reports from 2 different electronic health record systems in a large healthcare organization, and then externally validated on the reports of 2 other institutions with manually reviewed results as a benchmark. …”
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