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  1. 5701
    “…Four classification models, including XGBoost, naïve Bayes (NB), logistic regression (LR), and support vector machine (SVM) were constructed using the Python software. These four models were tested and compared for accuracy, F1 score, Matthews correlation coefficient (MCC), and area under the curve (AUC) of the receiver operating characteristic curves. …”
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    Predicting the Prognosis of Patients in the Coronary Care Unit: A Novel Multi-Category Machine Learning Model Using XGBoost
  2. 5702
    “…After this, we applied a backward feature selection model using R and Python to determine the most relevant variables. Three further analyses were done using variables selected from backward feature selection model (Dataset A), movement disorders specialist (Dataset B), and all the variables from the dataset (Dataset C). …”
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    Machine Learning Classifiers to Evaluate Data From Gait Analysis With Depth Cameras in Patients With Parkinson’s Disease
  3. 5703
    “…Finally, we developed SeqPatcher, a Python-based computational tool to analyse the trace files yielded by Sanger sequencing to generate consensus sequences, or take preanalysed consensus sequences in fasta format, and merge them with their corresponding whole-genome assemblies. …”
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    Targeted Sanger sequencing to recover key mutations in SARS-CoV-2 variant genome assemblies produced by next-generation sequencing
  4. 5704
    “…Learning to learn is an implementation of the L2L concept written in Python. This open-source software allows several instances of an optimization target to be executed with different parameters in an embarrassingly parallel fashion on HPC. …”
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    Online Artículo Texto
    Exploring Parameter and Hyper-Parameter Spaces of Neuroscience Models on High Performance Computers With Learning to Learn
  5. 5705
    “…In order to serve the scientific community, we have provided a Python-based pipeline to develop the prediction models using mutation profiles (VCF/MAF) of cancer patients. …”
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    Prediction of risk-associated genes and high-risk liver cancer patients from their mutation profile: benchmarking of mutation calling techniques
  6. 5706
    “…To address this, HFI data are exported into Excel by a PowerShell (v7.2) command-line script using Python (v3.10) with the REDCap API. Results are calculated with F# (v6.0) using Microsoft Excel Interop API and inserted into a report template with F# using the Microsoft Publisher Interop API. …”
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    511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets
  7. 5707
    “…Two different supervised ML approaches (i.e. multiclass classification and regression algorithms) are applied to the study dataset using Python v3.5 and WEKA, and tested by receiver operating curve (ROC) analysis. …”
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    331 A Machine Learning-based Pharmacogenomic Association Study of Major Adverse Cardiovascular Events (MACEs) in Caribbean Hispanic Patients on Clopidogrel
  8. 5708
    por Shaikh, Bilal, Smith, Lucian P, Vasilescu, Dan, Marupilla, Gnaneswara, Wilson, Michael, Agmon, Eran, Agnew, Henry, Andrews, Steven S, Anwar, Azraf, Beber, Moritz E, Bergmann, Frank T, Brooks, David, Brusch, Lutz, Calzone, Laurence, Choi, Kiri, Cooper, Joshua, Detloff, John, Drawert, Brian, Dumontier, Michel, Ermentrout, G Bard, Faeder, James R, Freiburger, Andrew P, Fröhlich, Fabian, Funahashi, Akira, Garny, Alan, Gennari, John H, Gleeson, Padraig, Goelzer, Anne, Haiman, Zachary, Hasenauer, Jan, Hellerstein, Joseph L, Hermjakob, Henning, Hoops, Stefan, Ison, Jon C, Jahn, Diego, Jakubowski, Henry V, Jordan, Ryann, Kalaš, Matúš, König, Matthias, Liebermeister, Wolfram, Sheriff, Rahuman S Malik, Mandal, Synchon, McDougal, Robert, Medley, J Kyle, Mendes, Pedro, Müller, Robert, Myers, Chris J, Naldi, Aurelien, Nguyen, Tung V N, Nickerson, David P, Olivier, Brett G, Patoliya, Drashti, Paulevé, Loïc, Petzold, Linda R, Priya, Ankita, Rampadarath, Anand K, Rohwer, Johann M, Saglam, Ali S, Singh, Dilawar, Sinha, Ankur, Snoep, Jacky, Sorby, Hugh, Spangler, Ryan, Starruß, Jörn, Thomas, Payton J, van Niekerk, David, Weindl, Daniel, Zhang, Fengkai, Zhukova, Anna, Goldberg, Arthur P, Schaff, James C, Blinov, Michael L, Sauro, Herbert M, Moraru, Ion I, Karr, Jonathan R
    Publicado 2022
    “…To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. …”
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    BioSimulators: a central registry of simulation engines and services for recommending specific tools
  9. 5709
    “…The software has been developed in Python using Numpy and Pandas and made freely available with an open-source MIT license to facilitate experimentation and further improvement (DOI 10.5281/zenodo.6513126). …”
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    Simplifying MS1 and MS2 spectra to achieve lower mass error, more dynamic range, and higher peptide identification confidence on the Bruker timsTOF Pro
  10. 5710
    “…Also, heat-map conceits between measured variables were calculated using the Python software. Key results indicate that drought stress led to significant reductions in all studied vegetative growth parameters (root and shoot biomasses) and photosynthetic pigments (chlorophyll a, b and total contents) while raised the levels of oxidative stress indicators. …”
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    Integral effects of brassinosteroids and timber waste biochar enhances the drought tolerance capacity of wheat plant
  11. 5711
    “…It involves creation of a Deep learning based Convolutional Neural Network (CNN) using Keras (python library) and integrating the model with a front-end user interface for ease of use. …”
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    CoviExpert: COVID-19 detection from chest X-ray using CNN
  12. 5712
    “…The files were converted to text files and two Python packages, SpaCy and TextStat were used to obtain the data presented here. …”
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    Improving access to COVID‐19 information by ensuring the readability of government websites
  13. 5713
    “…METHODS: UGC was extracted from Thrive With Me, a web app intervention for men living with HIV that includes an unstructured peer-to-peer support forum. In Python, topics were modeled by latent Dirichlet allocation. …”
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    Integrating Natural Language Processing and Interpretive Thematic Analyses to Gain Human-Centered Design Insights on HIV Mobile Health: Proof-of-Concept Analysis
  14. 5714
    “…A data processing pipeline was conducted using Python 3.8.9. RESULTS: The ASPPL course had 8,118 participants distributed across the five Brazilian regions. …”
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    The relevancy of massive health education in the Brazilian prison system: The course “health care for people deprived of freedom” and its impacts
  15. 5715
    por Uddin, Shahadat, Ong, Stephen, Lu, Haohui
    Publicado 2022
    “…In this illustration, existing data from an open-source data repository on construction projects and cost overrun frequencies was studied in which several machine learning models (Python’s Scikit-learn package) were tested and evaluated. …”
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    Machine learning in project analytics: a data-driven framework and case study
  16. 5716
    “…Statistical analysis was performed using SPSS 24.0, and least absolute shrinkage and selection operator (LASSO) regression model was established by Python 3.8.1 to minimise the effect of multicollinearity. …”
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    Analysing the influencing factors on caregivers’ burden among amyotrophic lateral sclerosis patients in China: a cross-sectional study based on data mining
  17. 5717
    “…BioTEA is an R-coded pipeline, wrapped in a Python-based command line interface and containerized with Docker technology. …”
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    BioTEA: Containerized Methods of Analysis for Microarray-Based Transcriptomics Data
  18. 5718
    “…To help overcome this bottleneck, we present TIAToolbox, a Python toolbox designed to make computational pathology accessible to computational, biomedical, and clinical researchers. …”
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    TIAToolbox as an end-to-end library for advanced tissue image analytics
  19. 5719
    “…CONCLUSION: We implemented a python program of pHisPred, which is freely available for non-commercial use at https://github.com/xiaofengsong/pHisPred. …”
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    pHisPred: a tool for the identification of histidine phosphorylation sites by integrating amino acid patterns and properties
  20. 5720
    “…Molecular docking analysis was conducted using the “Vina Wizard” program in PyRx-Python Prescription 0.8. RESULTS: Phytochemical analysis indicated that alkaloids, tannins, flavonoids, saponins, glycosides, and terpenoids were detected in the most bioactive crude extracts, whereas alkaloids, terpenoids, saponins, and gums were found in bioactive n-hexane fraction and steroids, glycosides, and terpenoids were found positive in chloroform fraction. …”
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    Identification of Potential Diuretic and Laxative Drug Candidates from Avicennia officinalis L. Bark through In Vivo Mice Model Studies and In Vitro Gas Chromatography-Mass Spectrometry and Molecular Docking Analysis
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