Prognostication of Recovery from Acute Stroke: R and Python Codes.
Published: 25 October 2022| Version 1 | DOI: 10.17632/h7jpngb92d.1
Contributors:
Yauhen Statsenko, , Description
1. The file titled "ich_plots_dlnm.Rmd" contains the code in R for calculating Spearman and Pearson's correlation coefficients as well as designing distributed lag non-linear models (DLNMs). 2. ich_prediction_nn notebook contains data analysis, feature importance estimation and prediction on stroke severity and outcomes (NHSS and MRS scores). Different models were used for prediction (namely, logistic regression, random forest, extra treees, ADAboost, SVC, and dense neural network).
Files
Institutions
United Arab Emirates University College of Medicine and Health Sciences
Categories
Linear Classifier, Correlation Coefficient, Patient Outcome, Prognostication, Linear Model, Distributed Lag Model