heart-disease-prediction-model

An end-to-end machine learning project built on the UCI Heart Disease dataset, covering data preprocessing, feature engineering, model training, evaluation, and deployment. The project includes Streamlit app that supports both single-patient and batch predictions, ensuring reproducibility through a well-structured pipeline and saved model artifacts

Heart Disease Prediction Application Using Machine Learning.

Join FirstNet Systems UK's Heart Disease Prediction Model project! Explore data relationships, visualize patterns, and build an accurate predictive model to combat heart disease. Let's make informed decisions and save lives through data analysis! 🩺❤️ #DataScience #Healthcare #HeartDiseasePrediction

Evaluación Comparativa de Algoritmos de Machine Learning para la Detección Temprana del Riesgo Cardiovascular. (Regresión Logística, Random Forest, LightGBM, XGBoost)

Machine learning-based heart disease prediction project conducted during the Patient Data Understanding course at Rowan University’s Master’s in Data Science program, Heart disease prediction project using ML models with 85% accuracy. Includes EDA, preprocessing, classification models and feature analysis.

Machine Learning-based Heart Disease Prediction system using feature selection (ANOVA, Chi-Square, Mutual Information) and ensemble models including Voting and Stacking classifiers with Flask deployment.

Clinical heart disease prediction system (MSc AI, BSBI). Uses supervised ML on patient vitals with a full diagnostic pipeline: normalization, feature analysis, and high-precision classification models for early-stage medical decision support.