• Nowsheen Rashid
• Dr. Neetu sharma

“Disease Prediction” system supported prophetical modeling predicts the unwellness of the user on the idea of the symptoms that user provides as associate degree input to the system. The system analyzes the symptoms provided by the user as input and provides the chance of the unwellness as associate degree output. Disease Prediction is finished by implementing three techniques like Support Vector Classifier, Decision Tree Classifier, and Random Forest Algorithms. These techniques calculate the probability of the unwellness. Therefore, average prediction accuracy eighty four percent is obtained

Heart Disease Prediction, Support Vector Classifier, Decision Tree Classifier, Random Forest Classifier, Machine learning..

"Use Of Machine Learning To Estimate Risk Of Cardiovascular Diseases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.214-216, May-2020, Available :http://www.jetir.org/papers/JETIR2005340.pdf

"Use Of Machine Learning To Estimate Risk Of Cardiovascular Diseases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 5, page no. pp214-216, May-2020, Available at : http://www.jetir.org/papers/JETIR2005340.pdf