Abstract
Applying data mining in the medical field is a very challenging undertaking due to the idiosyncrasies of the medical profession. By introducing status and progress of data mining and analyzing characteristics of medical data, a mathematical model of medical data mining based on computation intelligence such as data preprocessing, statistical techniques, artificial neural network, decision tree and manifold learning have been introduced. This paper focusing on data mining on clinical datasets, examining of high risk population with hypertension, cancer and child obesity etc., the main objective of data mining in clinical data warehouse had been an appropriate and sufficiently sensitive method to analyze the outcomes of effective treatments and reduce costs. Medical diagnosis is extremely important but complicated task that should be performed accurately and efficiently. In contrast, the slight difference could change the balance between life or death. Towards this direction, in this study a context-aware approach is proposed, aiming to provide medical supervisors with a series of applications and personalized services targeted to exploit the multi parameter analysis for the assessment of medical –related risk factors targeting in the reduction of diseases.
Keywords: Data Mining, Clinical data, Regression Analysis, Artificial Neural Network, Decision Tree
Full Issue
| View or download the full issue | PDF 56-65 |