A Survey on Machine Learning Models for Heart and Cardiovascular Disease Prediction

It can be concluded form the previous discussions that several challenges remain in applying machine learning models to cardiovascular disease prediction. One major issue is the availability and quality of medical datasets. Many datasets used in research are relatively small or limited to specific populations, which may affect the generalization of models in real-world clinical environments. Additionally, concerns related to model interpretability, data privacy, and clinical validation must be addressed before these systems can be widely adopted in healthcare. Machine learning and deep learning techniques have significantly improved the prediction and early detection of heart and cardiovascular diseases.

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