Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform
Open Access
- 5 January 2016
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 11 (1), e0145791
- https://doi.org/10.1371/journal.pone.0145791
Abstract
With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner’s Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research.Keywords
This publication has 43 references indexed in Scilit:
- Accessing the public MIMIC-II intensive care relational database for clinical researchBMC Medical Informatics and Decision Making, 2013
- Multiparameter Intelligent Monitoring in Intensive Care II: A public-access intensive care unit database*Critical Care Medicine, 2011
- LIBSVMACM Transactions on Intelligent Systems and Technology, 2011
- KNIME - the Konstanz information minerACM SIGKDD Explorations Newsletter, 2009
- MapReduceCommunications of the ACM, 2008
- Evolutionary tuning of multiple SVM parametersNeurocomputing, 2005
- Understanding Disability in Mental and General Medical ConditionsAmerican Journal of Psychiatry, 2000
- Wrappers for feature subset selectionArtificial Intelligence, 1997
- Support-vector networksMachine Learning, 1995
- A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter studyJAMA, 1993