Mar 2, 2025 · 📌 Overview This dataset is designed for predicting stroke risk using symptoms, demographics, and medical literature-inspired risk modeling. Version 2 significantly improves …

Performing clustering on stroke patients based on NIHSS data. This is the official repository for the research paper

An analysis of 312 patients with acute ischemic stroke who were treated with tPA found that an NIHSS score ≥ 20 was associated with a 17% rate of intracerebral hemorrhage, while a score …

This repository includes scripts to process and analyze images from all 1714 acute individuals with suspected stroke (with 1449 having stroke confirmed) in the Stroke Outcome Optimization …

This dataset includes anonymized images, behavioral measures and demographic details from a cohort of individuals from South Carolina with acute stroke. The fully BIDS-compatible dataset …

Apr 14, 2025 · This project uses a stroke prediction dataset from the healthcare domain. The goal is to analyze patient records to identify key risk factors and predict the likelihood of a stroke …

Analysis of stroke patient data to study the impact of thrombolysis treatment on outcomes. Includes statistical tests (Kruskal-Wallis, Mann-Whitney U, Chi-Square) to evaluate …

This repository contains a Jupyter Notebook detailing an in-depth exploratory data analysis (EDA) and preprocessing pipeline for the Kaggle Stroke Prediction dataset. The project's mission is …

Jul 1, 2025 · This project presents a comprehensive statistical, machine learning, and clustering analysis on a stroke prediction dataset. The analysis follows a structured pipeline starting from …

Stroke Risk Dataset based on Symptoms 📌 Overview The Stroke Risk Prediction Dataset is a comprehensive dataset designed for machine learning and medical research purposes. It …

Stroke Dataset Machine Learning This repository presents a complete machine learning workflow built on the Stroke Prediction Dataset. The project focuses on predicting stroke risk by …

About Stroke and the Dataset A stroke is a condition where the blood flow to the brain is decreased, causing cell death in the brain. One can roughly classify strokes into two main …

About Stroke Prediction for Preventive Intervention: Developed a machine learning model to predict strokes using demographic and health data. Achieved high recall for stroke cases. …

11 clinical features for predicting stroke events. Contribute to ramainvicta/stroke-prediction development by creating an account on GitHub.

The project titled “DATA ANALYSIS ON STROKE PREDICTION” is under category “Healthcare”, which inspects the patient’s medical information performed across various hospitals. The …

Healthcare-Dataset-Stroke-Set The dataset can be utilized to develop predictive models or algorithms to identify individuals at higher risk of experiencing a stroke.

Mar 14, 2025 · This project aims to predict stroke occurrences based on various health parameters and demographic data. It includes a detailed Healthcare Stroke Analysis …

🧠 Stroke Prediction for Early Intervention & Patient Stratification This project applies machine learning to predict stroke risk based on patient health records, helping healthcare providers …

Contribute to yamacdikmen/Stroke-Prediction development by creating an account on GitHub.

Factors such as age, body mass index, smoking status, average glucose level, hypertension, heart disease, and body mass index are critical risk factors for stroke. This study uses the …