Empirical Study on Applications of Data Mining Techniques in Healthcare

Abstract

Abstract:The healthcare environment is generally perceived as being 'information rich' yet 'knowledge poor'. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain. Valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, we briefly examine the potential use of classification based data mining techniques such as Rule based, decision tree and Artificial Neural Network to massive volume of healthcare data. In particular we consider a case study using classification techniques on a medical data set of diabetic patients.

Methodologies of Data Mining in Healthcare: A Inspection

“…In order to construct the linear model, linear function is utilized by linear regression. But there is limitation while we use linear approach because both types of variables are known already and hence, its main purpose is to trace a line that correlates between both these variables [46]. We cannot use linear regression for categorized data.…”

“…Before the introduction of decision trees and the Support Vector Machine (SVM) it was regarded as the best classification algorithm [43]. This was one of the reasons which encouraged NN as the most widely used classification algorithm in various biomedicine and healthcare fields [44,45,46]. For example, NN has been widely used as the algorithm supporting the diagnosis of diseases including cancers [47][48][49][50][51] and predict outcomes [52][53][54].…”

Prediction of Cardiac Arrhythmia using Artificial Neural Network

“…Iffat A. Gheyas et al [17] compared GRNN ensemble with existing algorithms (ARIMA & GARCH, MLP, GRNN with a single predictor and GRNN with multiple predictors) for forecasting univariate time series. Harleen Kaur et al [18] presented a case study of application of data mining and analysis to data of children with Diabetes mellitus and Diabetes insipidus.…”

Data Mining for diagnosis in Healthcare Sector-a review

“…These neurons are interconnected and within the network they worked together in parallel in order to produce the output functions. Neural network is the most widely used classification algorithm in various biomedicine and healthcare fields [7] [8] [9]. For example, NN has been widely used as the algorithm supporting the diagnosis of diseases including cancers [10] [11] [12] [13] [14]and predict outcomes [15] [16] [17].…”