Prognostication of Recovery from Acute Stroke: R and Python Codes

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).