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http://www.cs.uky.edu/~goldsmit/cdm/DMCDSS.pdf
a large number of applications that have included both data mining and clinical decision support systems. Decision support systems refer to a class of computer-based systems that aids the process of decision making.6 Table 3.1 lists some examples of decision support systems that utilize data mining tools in healthcare settings.Cited by: 29
https://healthitanalytics.com/news/the-difference-between-clinical-decision-support-big-data-analytics
Aug 31, 2017 · August 31, 2017 - Healthcare organizations have a lot of options to choose from when it comes to leveraging their growing big data assets.. From population health platforms and supply chain management tools to clinical decision support and business intelligence systems, there is no shortage of health IT companies offering their latest and greatest products to help alleviate some of the many ...
https://www.researchgate.net/publication/226764776_Data_Mining_and_Clinical_Decision_Support_Systems
Data Mining and Clinical Decision Support Systems With the advent of computing power and medical technology , large data sets as well as diverse and elaborate methods for data classification have
https://link.springer.com/chapter/10.1007%2F978-0-387-38319-4_3
Data mining is a process of pattern and relationship discovery within large sets of data. The context encompasses several fields, including pattern recognition, statistics, computer science, and database management. Thus the definition of data mining largely depends …Cited by: 29
https://link.springer.com/chapter/10.1007%2F978-3-319-31913-1_3
Jul 27, 2016 · This chapter discusses a variety of data mining techniques that have been used to develop clinical decision support systems, including decision trees, neural networks, logistic regression, nearest neighbor classifiers.Cited by: 29
https://healthitanalytics.com/features/understanding-the-basics-of-clinical-decision-support-systems
Dec 12, 2017 · December 12, 2017 - Clinical decision support systems are quickly becoming essential tools for healthcare providers as the volume of available data increases alongside their responsibility to deliver value-based care.. Reducing clinical variation and duplicative testing, ensuring patient safety, and avoiding complications that may result in expensive hospital readmissions are top priorities ...
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