Source code of 5001 Individual Project
Project description: Description Kidney transplantation is the optimal treatment to cure patients with end-stage renal disease (ESRD). However, infectious complication, especially pneumonia, is the main cause of mortality in the early stage. In this in-class project, we aimed to study the association between collected patient immune status features during immune monitoring and pneumonia in kidney transplant patients through machine learning models.
The immune status features consist of the percentages and absolute cell counts of CD3+CD4+ T cells, CD3+CD8+ T cells, CD19+ B cells and natural killer (NK) cells, and median fluorescence intensity (MFI) of human leukocyte antigen (HLA)-DR on monocytes and CD64 on neutrophils. Also, basic information including age and sex is provided. The task is to predict whether the patient will get pneumonia after the kidney transplantation.