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Activity Number: 159 - Novel Approaches for Diagnostics and Prediction with Complex Data
Type: Topic Contributed
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: International Chinese Statistical Association
Abstract #302935
Title: Statistical Monitoring of Hemodialysis Treatments via Raman Spectral Analysis
Author(s): Pang Du* and Yunnan Xu
Companies: Virginia Tech and Virginia Tech

Hemodialysis is a common dialysis procedure for patients whose kidneys can no longer remove enough waste and fluid from the blood. The standard hemodialysis treatment, with 4 hours each session and 3 sessions each week, is a long, painful and costly process for patients. Particularly, the uniform 4-hour duration completely ignores the receptiveness difference between patients. In this work, we propose to monitor the progress of a hemodialysis treatment through the analysis of Raman spectra of used dialysate. Each Raman spectrum represents the molecular composition of a used dialysate sample. Therefore we consider a functional data modeling of the spectra and develop a testing procedure that can detect significant molecular composition changes from one sample to the other. The theoretical and numerical studies on the properties of the test statistic will be provided.

Authors who are presenting talks have a * after their name.

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