Tag: ANN
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Early Heart Attack Prediction using ECG Autoencoder and 19 ML/AI Models with Test Performance QC Comparisons
Globally, cardiovascular disease (CVD) is the primary cause of morbidity and mortality, accounting for more than 70% of all fatalities. Machine learning (ML) can be used to predict the risk of a heart attack. The algorithms used for this task would be supervised ML algorithms, such as Random Forest, Logistic Regression, Support Vector Machines, etc.…
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Using AI/ANN AUC>90% for Early Diagnosis of Cardiovascular Disease (CVD)
The project utilizes AI-driven cardiovascular medicine with a focus on early diagnosis of heart disease using Artificial Neural Networks (ANN). Aiming to improve early detection of heart issues, the project processed a dataset of 303 patients using Python libraries and conducted extensive exploratory data analysis. A Sequential ANN model was subsequently built, revealing excellent performance…
