Stroke: Statistical analysis of risk factors and creation of predictive models using machine learning

An end-to-end machine learning project for stroke prediction

A web based application to predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status. Each row in the data provides relevant information about the patient.

Predict whether you'll get stroke or not !!

Stroke analysis, dataset - https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset. For analysis i used: mlp classifier, k-means clustering, k-neighbors classifier. Libraries: tensorflow, scikit-learn.

🥈🎉 Silver Award Winner and Presented at IEEE Conference 📝 .This project implements a comprehensive pipeline for real-time ECG (Electrocardiogram) data processing and analysis, integrating IoT devices.

2022년 1학기 개인 프로젝트 : 뇌졸증 환자 예측 모델·분석

Mechine Learnig | Stroke Prediction

Comparison of Machine Learning and Deep Learning Techniques for Stroke Prediction

Regression Analysis using dataset from different Industries

Repository code of classifying stroke dataset with classification machine learning algorithm including linear support vector machines and logistic regression.

Stroke Prediction App

Stroke Prediction System Using ML

First place solution for "medicine" topic in AI Challenge 2023

Evaluate stroke risk using logistic regression and decision tree models

Project work on #Healthcare_stroke_prediction using #MySQL

The project aims at displaying the charts/plots of the number of people affected by stroke based on the input parameters like smoking status, high blood pressure level, Cholesterol level, obesity level in some of the countries.

A patient's chance of stroke was predicted using analysis of a medical dataset. Project conducted in collaboration with a partner, Phillis Duong.