Designing an Intelligent Heart Disease Prediction System Via Data Mining Techniques

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Sharabiani, Ashkan | 2011

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 41997 (01)
University: Sharif University of Technology
Department: Industrial Engineering
Advisor(s): Shavandi, Hassan
Abstract:
The healthcare industry collects huge amounts of healthcare data which, unfortunately, are not“mined” to discover hidden information for effective decision making. Discovery of hidden patterns and relationships often goes nexploited. Advanced data mining techniques can help remedy this situation. The diagnosis of diseases is a vital and intricate job in medicine. The recognition of heart disease from diverse features or signs is a multi-layered problem that is not free from false assumptions and is frequently accompanied by impulsive effects. Thus the attempt to exploit knowledge and experience of several specialists and clinical screening data of patients composed in databases to assist the diagnosis procedure is regarded as a valuable option.This research has developed a prototype Hierarchial Hybrid Intelligent Heart Disease Prediction System using data mining techniques, namely, Naïve Bayes and Neural Network. Results show that this model outperforms the famous data mining predictive techniques
Keywords:
Data Mining ; Integrated Model ; Intelligent Systems