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Welcome

Welcome to PRECISION-LVAD tutorial!In this tutorial, we’ll be learning :

  • Load datasets
  • Fit personalized model on each pump parameter based on PRECISION-LVAD engine
  • Get Out-of-control points for each time-point
  • Evaluate the results

This srepository is linked to our new paper entitled:paper

Prerequisites

To run the PRECISION-LVAD algorithm you need to install below packages:

  • dplyr
  • Lme4
  • qcc

Load data

# loading the datasets:
df_all_patient<-readr::read_csv("data/syn_data_CA.csv")
head(df_all_patient)
# loading the datasets:
df_all_patient<-readr::read_csv("data/syn_data_MB.csv")
head(df_all_patient)
# loading the datasets:
admission_file<-readr::read_csv("data/admission_file.csv")
head(admission_file)
# loading the datasets:
pws_patient<-readr::read_csv("data/stable_patient.csv")
head(pws_patient)
df_all_patient$Datetime<- as.Date(df_all_patient$Datetime)
pws_patient$Datetime<- as.Date(pws_patient$Datetime)

Fit PRECISION-LVAD on the data

df_all_patient<-readr::read_csv("data/syn_data_CA.csv")
admission_file<-readr::read_csv("data/admission_file.csv")

df<-patient_specific_residual(variable_name = "Flow",
                              df_all_patient = df_all_patient)

head(df)

Obtain Out-of-control points with PRECISION-LVAD

Evaluate

Tutorial of PRECISION-LVAD!