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cardiovascular-disease

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The RNN for Cardiovascular Disease Detection project is an innovative application of deep learning techniques to detect and predict cardiovascular diseases using recurrent neural networks (RNNs). Built using Python, TensorFlow, and Keras, this project aims to provide a reliable tool for early detection and diagnosis of cardiovascular diseases.

  • Updated May 24, 2023
  • Jupyter Notebook

A robust heart disease risk assessment tool built with Python and Streamlit. Utilizes an Ensemble Stacking Classifier (Random Forest, XGBoost, SVM) to predict cardiovascular disease with high accuracy, complete with interactive visualizations and medical insights.

  • Updated Dec 4, 2025
  • Jupyter Notebook

Comprehensive collection of 8 clinical data science and health analytics projects focusing on disease prediction, risk stratification, and treatment pattern analysis using advanced machine learning algorithms and statistical modeling. Portfolio: https://nana-safo-duker.github.io/

  • Updated Nov 14, 2025
  • Jupyter Notebook

Stress driven glutamate, calcium, and ROS disease pathway research with a focus on transgenerational heritability. Source vault for the Biolectrics Wiki.

  • Updated Dec 8, 2025
  • TypeScript

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