Provides tools for mapping International Classification of Diseases codes to comorbidity, 
    enabling the identification and analysis of various medical conditions within healthcare data.

Provides an estimator for generalized linear models with incomplete
    data for discrete covariates. The estimation is based on the EM algorithm by the
    method of weights by Ibrahim (1990) <DOI:10.2307/2290013>.

Categorization and scoring of injury severity typically involves
    trained personnel with access to injured persons or their medical records. 'icdpicr' contains a function
    that provides automated calculation of Abbreviated Injury Scale ('AIS') and Injury Severity Score ('ISS')
    from International Classification of Diseases ('ICD') codes and may be a useful substitute to manual injury 
    severity scoring. 'ICDPIC' was originally developed in 'Stata', and 'icdpicr' is an open-access update 
    that accepts both 'ICD-9' and 'ICD-10' codes.

Identify Cancer Dysfunctional Sub-pathway by integrating gene expression, DNA methylation and copy number variation, and pathway topological information. 1)We firstly calculate the gene risk scores by integrating three kinds of data: DNA methylation, copy number variation, and gene expression.  2)Secondly, we perform a greedy search algorithm to identify the key dysfunctional sub-pathways within the pathways for which the discriminative scores were locally maximal. 3)Finally, the permutation test was used to calculate statistical significance level for these key dysfunctional sub-pathways.

Implements Individual Conditional Expectation (ICE) plots, a tool for visualizing the model estimated by any supervised learning algorithm. ICE plots refine Friedman's partial dependence plot by graphing the functional relationship between the predicted response and a covariate of interest for individual observations. Specifically, ICE plots highlight the variation in the fitted values across the range of a covariate of interest, suggesting where and to what extent they may exist.