This project is accepted under IEEE conference: https://www.icimia.in/ This project can efficiently detect CVDs based various parameters. It achived a 95% of accuracy and above 90% of Precision, Recall and F1-score. Distribution of code or using it without prior permission can be lead to legal issues. The dataset is present in Kaggle as well as in this project directory. The Kaggle link for the dataset: https://www.kaggle.com/datasets/alexteboul/heart-disease-health-indicators-dataset/data Published research paper: https://ieeexplore.ieee.org/abstract/document/10426035/
susmitsekharbhakta / ensemble-based-cvd-detection Goto Github PK
View Code? Open in Web Editor NEWA detailed comparative analysis with proposed best model to detect CVDs early
Home Page: https://ieeexplore.ieee.org/abstract/document/10426035
License: Creative Commons Zero v1.0 Universal