R package implementing an Evolutionary Monte-Carlo Markov Chain algorithm (an adaptation of Metropolis-Hastings). This package is designed to be used with medical data, especially with patients using medications.
Supervisor : Mr. Birmele Etienne
First of all you have to clone the emcAdr GitHub repository which is available here. Then you can install the package using the following command in the R console :
install.packages("~/path/to/emcAdr/package_src/emcAdr_1.0.tar.gz", repos = NULL, type = "source")The algorithm uses a modified medication tree which include an upper
bound that locates the last drug in the drug family represented by the
current node (if the current node is not a leaf). You can find the
original drugs tree in the emcAdr/data folder. You can also
use your own tree but an upper bound for each node is
mandatory (the upper bound of a leaf is the index of
this leaf in your 2D array).
The algorithm requires a data frame of patient. Every line of this Data frame represents a single patient, the medications they are taking and a boolean representing whether they have the adverse drug effect under consideration.
They are 2 mandatory columns : patientATC and patient ADR. Respectively the index of the drugs taken by the patient in the tree of drugs (indexes start at 0) and the boolean representing whether he has the ADR.
There is an example of a row for a patient who takes 3 drugs (having 12, 56 and 798 as indexes) and doesn’t have the adverse drug reaction under consideration :
| patientATC | patientADR |
|---|---|
| 12, 56, 798 | 0 |
You are now ready to use the EMC function contained in the package. Here is an example
res <- EMC(n = 100,nbIndividuals = 5,ATCtree = ATC_Tree_UpperBound_2014, observations = simulPatient_df, startingIndividuals = c(), startingTemperatures = c())