Heart disease detection using AI and ML

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Suyog Dilip Late; Prof. Nilesh Pardeshi

Heart disease detection using AI and ML

Authors: Suyog Dilip Late, Prof. Nilesh Pardeshi

Unique Paper ID: 177117
Volume: 11
Issue: 12
PageNo: 191-194

Keywords: Heart Disease Prediction Machine Learning Artificial Intelligence SVM Deep Learning Healthcare Analytics.

Abstract:
Heart disease is one of the leading causes of mortality worldwide. Early detection and accurate diagnosis can significantly reduce the risk of fatal outcomes. This research presents an AI and ML-based predictive model that analyzes medical data to classify patients based on their likelihood of having heart disease. The model utilizes machine learning techniques, including Decision Trees, Random Forest, Support Vector Machine (SVM), and Deep Learning models, to provide an efficient and accurate diagnosis. The dataset used in this study includes patient health parameters such as age, blood pressure, cholesterol levels, heart rate, and other vital indicators. Feature engineering techniques have been applied to refine the dataset, and hyperparameter tuning has been used to optimize the models. Experimental results indicate that the AI-driven model achieves an accuracy of over 90%, making it a reliable tool for heart disease prediction. This research demonstrates the potential of machine learning in healthcare, aiding medical professionals in early diagnosis and treatment planning.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 191-194

Heart disease detection using AI and ML

Available:https://ijirt.org/article?manuscript=177117

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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