Stroke is a disease that affects the arteries leading to and within the brain. A stroke occurs when a blood vessel that carries oxygen and nutrients to the brain is either blocked by a clot or ruptures. According to the WHO, stroke is the 2nd leading cause of death worldwide. Globally, 3% of the population are affected by subarachnoid hemorrhage…

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

Predict whether you'll get stroke or not !!

Detection (Prediction) of the possibility of a stroke in a person

Implementation of the study: "The Use of Deep Learning to Predict Stroke Patient Mortality" by Cheon et al.

Stroke-GFCN: segmentation of Ischemic brain lesions

🥈🎉 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.

DATA SCIENCE PROJECT ON STROKE PREDICTION- deployment link below 👇⬇️

Comprehensive notes, practical exercises, and problem-solving solutions from the Applied Data Science course, covering data preprocessing, machine learning algorithms, statistical analysis, data visualization, and real-world applications.

Stroke prediciton with EDA, data preprocessing, model building and sampling

Stroke Prediction Using Machine Learning (Classification use case)

machine learning model to predict individuals chances of having a stroke. See users view of app here: https://ml-stroke-predictions.herokuapp.com/

Comparing 10 different ML classifiers and using the one having best accuracy to predict the stroke risk to user. Fetching user details through web app hosted using Heroku.

Mechine Learnig | Stroke Prediction

Neural network to predict strokes.

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.

My first stroke prediction machine learning logistic regression model building in ipynb notebook using python.

A PyTorch model with 99.96% accuracy used for determining stroke risk, based on 16 established risk factors documented in leading medical textbooks, research papers, and guidelines from health organizations.

Healthalyze is an AI-powered tool designed to assess your stroke risk using deep learning. With just a few inputs—such as age, blood pressure, glucose levels, and lifestyle habits our advanced CNN model provides an accurate probability of stroke occurrence.