Knowledge Discovery and Data Mining Applications in the Healthcare Industry

2016 ◽  
pp. 1097-1118 ◽  
Author(s):  
Iman Barazandeh ◽  
Mohammad Reza Gholamian

The healthcare industry is one of the most attractive domains to realize the actionable knowledge discovery objectives. This chapter studies recent researches on knowledge discovery and data mining applications in the healthcare industry and proposes a new classification of these applications. Studies show that knowledge discovery and data mining applications in the healthcare industry can be classified to three major classes, namely patient view, market view, and system view. Patient view includes papers that performed pure data mining on healthcare industry data. Market view includes papers that saw the patients as customers. System view includes papers that developed a decision support system. The goal of this classification is identifying research opportunities and gaps for researchers interested in this context.

Author(s):  
Iman Barazandeh ◽  
Mohammad Reza Gholamian

The healthcare industry is one of the most attractive domains to realize the actionable knowledge discovery objectives. This chapter studies recent researches on knowledge discovery and data mining applications in the healthcare industry and proposes a new classification of these applications. Studies show that knowledge discovery and data mining applications in the healthcare industry can be classified to three major classes, namely patient view, market view, and system view. Patient view includes papers that performed pure data mining on healthcare industry data. Market view includes papers that saw the patients as customers. System view includes papers that developed a decision support system. The goal of this classification is identifying research opportunities and gaps for researchers interested in this context.


2018 ◽  
pp. 2161-2182
Author(s):  
Iman Barazandeh ◽  
Mohammad Reza Gholamian

The healthcare industry is one of the most attractive domains to realize the actionable knowledge discovery objectives. This chapter studies recent researches on knowledge discovery and data mining applications in the healthcare industry and proposes a new classification of these applications. Studies show that knowledge discovery and data mining applications in the healthcare industry can be classified to three major classes, namely patient view, market view, and system view. Patient view includes papers that performed pure data mining on healthcare industry data. Market view includes papers that saw the patients as customers. System view includes papers that developed a decision support system. The goal of this classification is identifying research opportunities and gaps for researchers interested in this context.


2015 ◽  
Vol 15 (1) ◽  
pp. 31-50 ◽  
Author(s):  
Hela Ltifi ◽  
Emna Ben Mohamed ◽  
Mounir ben Ayed

The article aims to present a generic interactive visual analytics solution that provides temporal decision support using knowledge discovery from data modules together with interactive visual representations. It bases its design decisions on classification of visual representation techniques according to the criteria of temporal data type, periodicity, and dimensionality. The design proposal is applied to an existing medical knowledge discovery from data–based decision support system aiming at assisting physicians in the fight against nosocomial infections in the intensive care units. Our solution is fully implemented and evaluated.


2014 ◽  
Vol 5 (2) ◽  
pp. 39-61 ◽  
Author(s):  
Ricardo Anderson ◽  
Gunjan Mansingh

Knowledge discovery and data-mining techniques have the potential to provide insights into data that can improve decision making. This paper explores the use of data mining to extract patterns from data in the domain of social welfare. It discusses the application of the Integrated Knowledge Discovery and Data Mining process model (IKDDM) a social welfare programme in Jamaica. Further, it demonstrates how the knowledge acquired from the data is used to develop a knowledge driven decision support system (DSS) in the PATH CCT programme. This system was successfully tested in the domain showing over 94% accuracy in the comparative decisions produced.


Sign in / Sign up

Export Citation Format

Share Document