Query-constraint-based mining of association rules for exploratory analysis of clinical datasets in the National Sleep Research Resource
@article{Abeysinghe2018QueryconstraintbasedMO, title={Query-constraint-based mining of association rules for exploratory analysis of clinical datasets in the National Sleep Research Resource}, author={Rashmie Abeysinghe and Licong Cui}, journal={BMC Medical Informatics and Decision Making}, year={2018}, volume={18} }
BackgroundAssociation Rule Mining (ARM) has been widely used by biomedical researchers to perform exploratory data analysis and uncover potential relationships among variables in biomedical datasets. However, when biomedical datasets are high-dimensional, performing ARM on such datasets will yield a large number of rules, many of which may be uninteresting. Especially for imbalanced datasets, performing ARM directly would result in uninteresting rules that are dominated by certain variables…
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References
SHOWING 1-10 OF 57 REFERENCES
Query-constraint-based association rule mining from diverse clinical datasets in the national sleep research resource
- Computer Science2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
- 2017
A query-constraint-based ARM (QARM) approach is introduced for exploratory analysis of diverse clinical datasets integrated in the National Sleep Research Resource (NSRR), which enables the rule mining on a subset of data containing items of interest based on a query constraint.
Mammographic information analysis through association-rule mining
- Computer ScienceCanadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513)
- 2004
Preliminary results of the application of applying association-rule mining techniques to the U of C Atlas of Mammograms are described and a new breast mass classification method based on quantitative association- rule mining is proposed.
Identifying HotSpots in Lung Cancer Data Using Association Rule Mining
- Computer Science2011 IEEE 11th International Conference on Data Mining Workshops
- 2011
The goal here is to identify characteristics of patient segments where average survival is significantly higher/lower than average survival across the entire dataset, and to provide interesting insights into lung cancer survival.
Association rule discovery with the train and test approach for heart disease prediction
- Computer ScienceIEEE Transactions on Information Technology in Biomedicine
- 2006
An algorithm is introduced that uses search constraints to reduce the number of rules, searches for association rules on a training set, and finally validates them on an independent test set to produce a set of rules with high predictive accuracy.
Scaling Up Scientific Discovery in Sleep Medicine: The National Sleep Research Resource.
- Computer ScienceSleep
- 2016
The NSRR is a web-based data portal that aggregates, harmonizes, and organizes sleep and clinical data from thousands of individuals studied as part of cohort studies or clinical trials and provides the user a suite of tools to facilitate data exploration and data visualization.
Mining Top-K Association Rules
- Computer ScienceCanadian Conference on AI
- 2012
This work proposes an algorithm to mine the top-k association rules, where k is the number of association rules to be found and is set by the user, and utilizes a new approach for generating association rules named rule expansions and includes several optimizations.
Mining electronic health records: towards better research applications and clinical care
- MedicineNature Reviews Genetics
- 2012
The potential for furthering medical research and clinical care using EHR data and the challenges that must be overcome before this is a reality are considered.
icuARM-An ICU Clinical Decision Support System Using Association Rule Mining
- Medicine, Computer ScienceIEEE Journal of Translational Engineering in Health and Medicine
- 2013
An ICU clinical decision support system icuARM based on associate rule mining (ARM) and a publicly available research database MIMIC-II that contains more than 40,000 ICU records for 30,000+patients can provide valuable insights for ICU physicians to tailor a patient's treatment based on his or her clinical status in real time.
Mining Top-K Non-redundant Association Rules
- Computer ScienceISMIS
- 2012
This paper proposes an approximate algorithm named TNR for mining top-k non redundant association rules and addresses the problem of a large proportion of association rules generated are redundant.
Data Mining in Clinical Decision Support Systems for Diagnosis, Prediction and Treatment of Heart Disease
- Medicine, Computer Science
- 2013
This paper compares the performance and working of six CDSS systems which use different data mining techniques for heart disease prediction and diagnosis and finds out that there is no system to identify treatment options for HD patients.