Analytical Study of Diagnosis for Angioplasty and Stents Patients using Improved Classification Technique

The various technologies of data mining DM models for forecast of heart disease are discussed. Data mining plays an important role in building an intelligent model for medical systems to detect heart disease HD using data sets of Angioplasty and Stents patients, which involves risk factor associated with heart disease. Medical practitioners can help the patients by predicting the heart disease before occurring. The large data available from medical diagnosis is analyzed by using data mining tools and useful information known as knowledge is extracted. Mining is a method of exploring massive sets of data to take out patterns which are hidden and previously unknown relationships and knowledge detection to help the better understanding of medical data to prevent heart disease. There are many DM techniques available namely Classification techniques involving Naïve bayes NB , Decision tree DT , Neural network NN , Genetic algorithm GA , Artificial intelligence AI and Clustering algorithms like KNN, and Support vector machine SVM . Several studies have been carried out for developing prediction model using individual technique and also by combining two or more techniques. This research provides a quick and easy review and understanding of available prediction models using data mining. The comparison shows the accuracy level of each model given by different researchers. Faisal Riyaz Wani | Er. Harwinder Kaur "Analytical Study of Diagnosis for Angioplasty and Stents Patients using Improved Classification Technique" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd19169.pdf http://www.ijtsrd.com/computer-science/other/19169/analytical-study-of-diagnosis-for-angioplasty-and-stents-patients-using-improved-classification-technique/faisal-riyaz-wani