Using Data Mining for Prediction of Hospital Length of Stay: An Application of the CRISP-DM Methodology
نویسندگان
چکیده
1 HFAR Hospital das Foras Armadas, Azinhaga Ulmeiros, 1620-060 Lisboa, Portugal [email protected] 2 ALGORITMI Research Centre, Department of Information Systems, University of Minho, 4800-058 Guimarães, Portugal [email protected] WWW home page: http://www3.dsi.uminho.pt/pcortez 3 Business Research Unit (UNIDE-IUL), Instituto Universitário de Lisboa (ISCTE-IUL), Av. das Forças Armadas, 1629-026 Lisboa, Portugal [email protected]
منابع مشابه
Customer Retention Based on the Number of Purchase: A Data Mining Approach
Purpose: this study wants to find any relationship between the numbers of purchase and the income the customer brings to the company. The attempt is to find those customers who buy more than one life insurance policy and represent the signs of good payments at the same time by the help of data mining tools. Design/ methodology/ approach: the approach of this research is to use data mining tools...
متن کاملRetaining Customers Using Clustering and Association Rules in Insurance Industry: A Case Study
This study clusters customers and finds the characteristics of different groups in a life insurance company in order to find a way for prediction of customer behavior based on payment. The approach is to use clustering and association rules based on CRISP-DM methodology in data mining. The researcher could classify customers of each policy in three different clusters, using association rules. A...
متن کاملPersonal Credit Score Prediction using Data Mining Algorithms (Case Study: Bank Customers)
Knowledge and information extraction from data is an age-old concept in scientific studies. In industrial decision-making processes, the application of this concept gives rise to data-mining opportunities. Personal credit scoring is an ever-vital tool for banking systems in order to manage and minimize the inherent risks of the financial sector, thus, the design and improvement of credit scorin...
متن کاملDetermining Factors Influencing Length of Stay and Predicting Length of Stay Using Data Mining in the General Surgery Department
Background: Length of stay is one of the most important indicators in assessing hospital performance. A shorter stay can reduce the costs per discharge and shift care from inpatient to less expensive post-acute settings. It can lead to a greater readmission rate, better resource management, and more efficient services. Objective: This study aimed to ident...
متن کاملAdapting CRISP-DM Process for Social Network Analytics: Application to Healthcare
One of the key limitations about research involving big data is the lack of a sound methodological process that drives the conceptual and analytical questions posed to the data. In this study, we adapt the popular CRISP-DM process to analyze large volumes of unstructured data to generate analytical insights. We add specificity to the CRISP-DM methodology. Specifically, we propose “Cross Industr...
متن کامل