Title
Process Prediction in Noisy Data Sets: A Case Study in a Dutch Hospital.
Abstract
Predicting the amount of money that can be claimed is critical to the effective running of an Hospital. In this paper we describe a case study of a Dutch Hospital where we use process mining to predict the cash flow of the Hospital. In order to predict the cost of a treatment, we use different data mining techniques to predict the sequence of treatments administered, the duration and the final "care product" or diagnosis of the patient. While performing the data analysis we encountered three specific kinds of noise that we call sequence noise, human noise and duration noise. Studies in the past have discussed ways to reduce the noise in process data. However, it is not very clear what effect the noise has to different kinds of process analysis. In this paper we describe the combined effect of sequence noise, human noise and duration noise on the analysis of process data, by comparing the performance of several mining techniques on the data.
Year
DOI
Venue
2012
10.1007/978-3-642-40919-6_4
Lecture Notes in Business Information Processing
Keywords
Field
DocType
process prediction,process mining,classification,cash flow prediction,data noise,case study
Data mining,Noisy data,Work in process,Process analysis,Engineering,Cash flow,Data Noise,Process mining
Conference
Volume
ISSN
Citations 
162
1865-1348
13
PageRank 
References 
Authors
0.61
17
3
Name
Order
Citations
PageRank
sjoerd van der spoel1171.03
Maurice van Keulen269954.67
chintan amrit316019.11