Classification Model (End to End Classification of Heart Disease - UCI Data Set)

Heart Failure/Heart Disease Prediction through Statistical Analysis and Machine Learning

Classification models for heart disease prediction

CARDIOsetu is a web application designed to monitor individual heart health. It uses API integration to enable voice-to-text input for accessibility, making it easier for individuals with verbal and visual disabilities to interact with the app.

Predicting Mortality among a Cohort of patients with Heart Failure

Machine learning project seeks to identify patterns to determine if a certain patient has heart disease

A jupyter notebook walking through implementing rudimentary logistic regression. Dataset downloaded from Kaggle

Deploying a ML model using docker in Kubernetes

This project focuses on enhancing healthcare data security and privacy. We leveraged the Gaussian Differential Privacy (GDP) algorithm to protect individual patient information while enabling robust data analysis.

A comprehensive exploration of machine learning techniques and data science best practices applied to the UCI Heart Disease dataset. Focusing on data preprocessing, exploratory analysis, and predictive modelling to identify key factors in heart disease. Part of Big Data Management and Analytics (BDMA) program.

BEGINNER - This is a classification project for the subject "Data Mining" in the 3rd year of Statistics (SSE) at the University of Milano-Bicocca.

LPIII Mini Project

A service to connect patients and doctors.

Identification system for the molecular basis of coronary heart disease powered by AI ( Artificial Intelligence ) and machine learning algorithms.

Repository for KNN and KMeans algorithms.

Kaggle Dataset Analysis on Exploring Important Factors to Heart Disease

In the ipynb file I'm running multiple ML classifier and regression algorithm's

Code of the Cardiovascular Risk Prediction Project, which is used to identify risk factors for cardiovascular disease related to coronary heart disease and stroke in adults.

Applied Machine Learning Final Project