Association Rule Mining in Higher Education: A Case Study of Computer Science Students

2019 ◽  
pp. 311-328
Author(s):  
Njoud Alangari ◽  
Raad Alturki
Keyword(s):  
Higher Education ◽  
Computer Science ◽  
Association Rule ◽  
Association Rule Mining ◽  
Science Students ◽  
Rule Mining

scholarly journals Association Rules Mining for Hospital Readmission: A Case Study

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2706
Author(s):  
Nor Hamizah Miswan ◽  
‘Ismat Mohd Sulaiman ◽  
Chee Seng Chan ◽  
Chong Guan Ng
Keyword(s):  
Association Rule ◽  
Hospital Readmission ◽  
Association Rule Mining ◽  
Demographic Variables ◽  
Apriori Algorithm ◽  
Age Group ◽  
Rule Mining ◽  
Learning Rules ◽  
And Performance

As an indicator of healthcare quality and performance, hospital readmission incurs major costs for healthcare systems worldwide. Understanding the relationships between readmission factors, such as input features and readmission length, is challenging following intricate hospital readmission procedures. This study discovered the significant correlation between potential readmission factors (threshold of various settings for readmission length) and basic demographic variables. Association rule mining (ARM), particularly the Apriori algorithm, was utilised to extract the hidden input variable patterns and relationships among admitted patients by generating supervised learning rules. The mined rules were categorised into two outcomes to comprehend readmission data; (i) the rules associated with various readmission length and (ii) several expert-validated variables related to basic demographics (gender, race, and age group). The extracted rules proved useful to facilitate decision-making and resource preparation to minimise patient readmission.

Sign in / Sign up

Export Citation Format

Share Document