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@article{197006,
        author = {MANIKONDA CHARAN RAJ and NUNNA SAI VENKATA SATYA SIVA and NALAMOTHU VAMSI and MANIVANNAN},
        title = {AI-assisted Heart disease Prediction System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {10395-10402},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197006},
        abstract = {This project focuses on developing an AI-assisted Heart Disease Prediction System using machine learning techniques. The system analyses patient health parameters such as age, cholesterol level, blood pressure, heart rate, and other medical attributes to predict the presence of heart disease. The dataset used for this project contains multiple patient records and medical features, which are processed and analysed using Python and machine learning algorithms. The proposed system uses the Logistic Regression algorithm to train the model and make predictions. Data preprocessing, feature scaling, and model evaluation techniques are applied to improve prediction accuracy and reliability. The system generates diagnostic results that help healthcare professionals in faster and more consistent decision-making. The developed AI-based prediction system aims to reduce diagnosis time, minimize human errors, and provide reliable decision support for doctors. It can be useful in hospitals, telemedicine services, and rural healthcare centers where specialist availability is limited. Overall, this project demonstrates how Artificial Intelligence can enhance healthcare services and improve patient outcomes through early disease detection and intelligent data analysis.},
        keywords = {Artificial Intelligenc, Heart Disease Prediction, Machine Learning, Logistic Regression, Healthcare Analytics, Medical Data Analysis, Disease Diagnosis, Predictive Modelin, Data Preprocessing, Clinical Decision Support.},
        month = {April},
        }