Stroke prediction dataset github Dataset can also be found in this repository with the path . This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, and various diseases and smoking status. Project Overview: Dataset predicts stroke likelihood based on patient parameters (gender, age, diseases, smoking). machine-learning neural-network python3 pytorch kaggle artificial-intelligence artificial-neural-networks tensor kaggle-dataset stroke-prediction Updated Mar 30, 2022 Python This project predicts stroke disease using three ML algorithms - fmspecial/Stroke_Prediction According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths. It is used to predict whether a patient is likely to get stroke based on the input parameters like age, various diseases, bmi, average glucose level and smoking status. neural-networks tensor kaggle-dataset stroke-prediction Stroke and BMI have the strongest correlation with 0. Created March 22, 2023 21:03. core. . Acute Ischemic Stroke Prediction A machine learning approach for early prediction of acute ischemic strokes in patients based on their medical history. Contribute to TomerSh135/Stroke-Prediction-Dataset development by creating an account on GitHub. You signed in with another tab or window. Stroke Prediction Using Machine Learning (Classification use case) Topics machine-learning model logistic-regression decision-tree-classifier random-forest-classifier knn-classifier stroke-prediction Introduction¶ The dataset for this competition (both train and test) was generated from a deep learning model trained on the Stroke Prediction Dataset. ipynb data preprocessing (takeing care of missing data, outliers, etc. By detecting high-risk individuals early, appropriate preventive measures can be taken to reduce the incidence and impact of stroke. Impact: Stroke Prediction Dataset. Achieved high recall for stroke cases. The model aims to assist in early detection and intervention of strokes, potentially saving lives and improving patient outcomes. Contribute to arturnovais/Stroke-Prediction-Dataset development by creating an account on GitHub. 11 clinical features for predicting stroke events. healthcare-dataset-stroke-data. Dataset, thus can be exchanged with other datasets and loaders (At the moment there are two datasets with different transformations for training and validation). Input data is preprocessed and is given to over 7 models, where a maximum accuracy of 99. Contribute to rajannnnnnn/stroke-prediction-dataset development by creating an account on GitHub. The output attribute is a The dataset for the project has the following columns: id: unique identifier; gender: "Male", "Female" or "Other" age: age of the patient; hypertension: 0 if the patient doesn't have hypertension, 1 if the patient has hypertension Stroke Prediction Dataset. Optimized dataset, applied feature engineering, and implemented various algorithms. Mar 22, 2023 · GitHub Gist: instantly share code, notes, and snippets. This project utilizes the Stroke Prediction Dataset from Kaggle, available here. 2% classification accuracy via 5-fold cross validation approach. Hi all, This is the capstone project on stroke prediction dataset. You signed out in another tab or window. Navigation Menu Toggle navigation. ) available in preparation. BhanuMotupalli / Heart Stroke Prediction Dataset. Objective: Create a machine learning model predicting patients at risk of stroke. csv from the Kaggle Website, credit to the author of the dataset fedesoriano. Manage code changes Stroke Prediction for Preventive Intervention: Developed a machine learning model to predict strokes using demographic and health data. Contribute to agauna-hdz/Stroke-Prediction-Dataset development by creating an account on GitHub. hypertension: 0 if the patient doesn't have hypertension, 1 if the patient has hypertension #Hypothesis: people who had stroke is higher in bmi than people who had no stroke. There are more female than male in the data set. py is inherited from torch. Stroke Prediction This project goes through data exploration, cleaning and training of a neural network that uses entity embedding to map categorical variables. It gives users a quick understanding of the dataset's structure. Using SQL and Power BI, it aims to identify trends and corr The Dataset Stroke Prediction is taken in Kaggle. ; The system uses a 70-30 training-testing split. Skip to content. Implement an AI system leveraging medical image analysis and predictive modeling to forecast the likelihood of brain strokes. Navigation Menu Toggle navigation Contribute to TomerSh135/Stroke-Prediction-Dataset development by creating an account on GitHub. Contribute to manop-ph/stroke-prediction-dataset development by creating an account on GitHub. 47 - 2. The project is designed as a case study to apply deep learning concepts learned during the training period. The goal of this project was to explore the dataset, clean and preprocess the data, and perform basic statistical analysis and predictive modeling. - ajspurr/stroke_prediction This is Stroke Prediction Dataset. 1 development by creating an account on GitHub. 15,000 records & 22 fields of stroke prediction dataset, containing: 'Patient ID', 'Patient Name', 'Age', 'Gender', 'Hypertension', 'Heart Disease', 'Marital Status', 'Work Type Dataset Overview: The web app provides an overview of the Stroke Prediction dataset, including the number of records, features, and data types. Contribute to kevin-wijaya/Stroke-Sampling-Prediction development by creating an account on GitHub. csv; The dataset description is as follows: The dataset consists of 4798 records of patients out of which 3122 are males and 1676 are females. If not available on GitHub, the notebook can be accessed on nbviewer, or alternatively on Kaggle. Stroke Prediction Dataset by using Machine Learning - AsifIkbal1/-Stroke-Prediction-Dataset Contribute to marionette-P/Stroke-Prediction-Dataset development by creating an account on GitHub. Contribute to 9amomaru/Stroke-Prediction-Dataset development by creating an account on GitHub. Summary without Implementation Details# This dataset contains a total of 5110 datapoints, each of them describing a patient, whether they have had a stroke or not, as well as 10 other variables, ranging from gender, age and type of work An exploratory data analysis (EDA) and various statistical tests performed on a dataset focused on stroke prediction. ipynb as a Pandas DataFrame; Columns where the BMI value was "NaN" were dropped from the DataFrame Jun 13, 2021 · Download the Stroke Prediction Dataset from Kaggle and extract the file healthcare-dataset-stroke-data. - GitHub - sa-diq/Stroke-Prediction: Prediction of stroke in patients using machine learning algorithms. - ebbeberge/stroke-prediction 3) What does the dataset contain? This dataset contains 5110 entries and 12 attributes related to brain health. - ankitlehra/Stroke-Prediction-Dataset---Exploratory-Data-Analysis You need to download ‘Stroke Prediction Dataset’ data using the library Scikit learn; ref is given below. We aim to identify the factors that con The dataset used in the development of the method was the open-access Stroke Prediction dataset. Prediction of brain stroke based on imbalanced dataset in Stroke Prediction Dataset Context According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths. Sep 21, 2021 · <class 'pandas. list of steps in this path are as below: exploratory data analysis available in P2. This involves using Python, deep learning frameworks like TensorFlow or PyTorch, and specialized medical imaging datasets for training and validation. Stroke Prediction Dataset created through R. Contribute to kushal3877/Stroke-Prediction-Dataset development by creating an account on GitHub. frame. /Stroke_analysis1 - Stroke_analysis1. This package can be imported into any application for adding security features. Using SQL and Power BI, it aims to identify trends and corr To predict what factors influence a person’s stroke, I will utilize the stroke variable as the dependent variable. Hi all,. csv was read into Data Extraction. A dataset containing all the required fields to build robust AI/ML models to detect Stroke. Stroke Predictions Dataset. Contribute to sevesilvestre/StrokePredictionData development by creating an account on GitHub. Contribute to nithinp300/Stroke-Prediction-Dataset development by creating an account on GitHub. The dataset used in this project contains information about various health parameters of individuals, including: id: unique identifier; gender: "Male", "Female" or "Other" Write better code with AI Code review. Contribute to URJ5329/Stroke_Prediction_Dataset development by creating an account on GitHub. cerebral stroke prediction based on imbalanced medical dataset - Jdss026/stroke-classifier. to make predictions of stroke cases based on simple health 11 clinical features for predicting stroke events. - GitHub - erma0x/stroke-prediction-model: Data exploration, preprocessing, analysis and building a stroke model prediction in the life of the patient. Feature Selection: The web app allows users to select and analyze specific features from the dataset. In raw data various information such as person's id ,gender ,age ,hypertension ,heart_disease ,ever_married, work_type, Residence_type ,avg_glucose_level, bmi ,smoking_status ,stroke are given. To enhance the accuracy of the stroke prediction model, the dataset will be analyzed and processed using various data science methodologies and algorithms. This project utilized a dataset containing various patient characteristics, including demographics, health conditions, and lifestyle habits Aimed to identify individuals at higher risk of stroke for early intervention and preventative measures. The analysis includes linear and logistic regression models, univariate descriptive analysis, ANOVA, and chi-square tests, among others. Using SQL and Power BI, it aims to identify trends and corr Data Set Information: This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, and various diseases and smoking status. ; The system uses Logistic Regression: Logistic Regression is a regression model in which the response variable (dependent variable) has categorical values such as True/False or 0/1. Write better code with AI Security. GitHub repository for stroke prediction project. Analysis of the Stroke Prediction Dataset provided on Kaggle. gender: "Male", "Female" or "Other" age: age of the patient. This project describes step-by-step procedure for building a machine learning (ML) model for stroke prediction and for analysing which features are most useful for the prediction. this project contains a full knowledge discovery path on stroke prediction dataset. Divide the data randomly in training and testing Saved searches Use saved searches to filter your results more quickly Contribute to elleniayele/Stroke-Prediction-Dataset. The dataset consists of 11 clinical features which contribute to stroke occurence. Reload to refresh your session. It’s a crowd- sourced platform to attract, nurture, train and challenge data scientists from all around the world to solve data science, machine learning and predictive analytics problems. The API can be integrated seamlessly into existing healthcare systems Navigation Menu Toggle navigation. View Notebook Download Dataset Contribute to enot9910/Stroke-Prediction-Dataset development by creating an account on GitHub. Contribute to NabilRaiyan/Stroke-Prediction-Dataset development by creating an account on GitHub. Project Overview This project focuses on detecting brain strokes using machine learning techniques, specifically a Convolutional Neural Network (CNN) algorithm. Stroke Disease Prediction classifies a person with Stroke Disease and a healthy person based on the input dataset. Future Direction: Incorporate additional types of data, such as patient medical history, genetic information, and clinical reports, to enhance the predictive accuracy and reliability of the model. 42 Explanatory Data Analysis -Patients between the age of 50-80 years old are at greater risk of getting a stroke. 4% is achieved. This dataset has been used to predict stroke with 566 different model algorithms. csv. Initially an EDA has been done to understand the features and later More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. We tune parameters with Stratified K-Fold Cross Validation, ROC-AUC, Precision-Recall Curves and feature importance analysis. #Create two table: stroke people, normal people #At 99% CI, the stroke people bmi is higher than normal people bmi at 0. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Contribute to orkunaran/Stroke-Prediction development by creating an account on GitHub. stroke_prediction_dataset_and_WorkBook In this folder the raw dataset and workbook in excel is given. The rather simple neural network achieves approximately 98. Performing Various Classification Algorithms with GridSearchCV to find the tuned parameters - STROKE_PREDICTION_DATASET/README. I have done EDA, visualisation, encoding, scaling and modelling of dataset. This dataset was created by fedesoriano and it was last updated 9 months ago. Chastity Benton 03/2022 [ ] spark Gemini keyboard_arrow_down Task: To create a model to determine if a patient is likely to get a stroke In this project, we will attempt to classify stroke patients using a dataset provided on Kaggle: Kaggle Stroke Dataset. id: unique identifier. Context According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for This repository contains the code and resources for building a deep learning solution to predict the likelihood of a person having a stroke. Contribute to BrunoMeloSlv/Stroke-Prediction-Dataset development by creating an account on GitHub. utils. Contribute to enot9910/Stroke-Prediction-Dataset development by creating an account on GitHub. There are 12 primary features describing the dataset with one feature being the target variable. Feature distributions are close to, but not exactly the same, as the original. As per the WHO (World Health Organization) stroke is the 2nd leading cause of dead globally. Stroke are becoming more common among female than male; A person’s type of residence has no bearing on whether or not they have a stroke. This video showcases the functionality of the Tkinter-based GUI interface for uploading CT scan images and receiving predictions on whether the image indicates a brain stroke or not. ipynb Contribute to mnbpdx/stroke-prediction-dataset development by creating an account on GitHub. Analysis based 4 different machine learning models. Leveraged skills in data preprocessing, balancing with SMOTE, and hyperparameter optimization using KNN and Optuna for model tuning. GitHub community articles Repositories. The dataset under More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. You need to download ‘Stroke Prediction Dataset’ data using the library Scikit learn; ref is given below. data. 4) Which type of ML model is it and what has been the approach to build it? This is a classification type of ML model. Predicted stroke risk with 92% accuracy by applying logistic regression, random forests, and deep learning on health data. Machine Learning project using Kaggle Stroke Dataset where I perform exploratory data analysis, data preprocessing, classification model training (Logistic Regression, Random Forest, SVM, XGBoost, KNN), hyperparameter tuning, stroke prediction, and model evaluation. Mar 7, 2025 · Dataset Source: Healthcare Dataset Stroke Data from Kaggle. Resources The dataset used to predict stroke is a dataset from Kaggle. Brain Stroke Prediction- Project on predicting brain stroke on an imbalanced dataset with various ML Algorithms and DL to find the optimal model and use for medical applications. 98% accurate - This stroke risk prediction Machine Learning model utilises ensemble machine learning (Random Forest, Gradient Boosting, XBoost) combined via voting classifier. Contribute to Rasha-A21/Stroke-Prediction-Dataset development by creating an account on GitHub. Check out a prediction model that was built based on this dataset from here Also check out the code of this dataset from here 📌 Overview This dataset is designed for predicting stroke risk using symptoms , demographics , and medical literature-inspired risk modeling . Nov 1, 2022 · The dataset is highly unbalanced with respect to the occurrence of stroke events; most of the records in the EHR dataset belong to cases that have not suffered from stroke. CTrouton/Stroke-Prediction-Dataset This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Sign in Product Contribute to tejaharshini4455/Stroke_Prediction_Dataset development by creating an account on GitHub. Contribute to Shettyprateeksha/Stroke-Prediction-Dataset- development by creating an account on GitHub. Find and fix vulnerabilities Libraries Used: Pandas, Scitkitlearn, Keras, Tensorflow, MatPlotLib, Seaborn, and NumPy DataSet Description: The Kaggle stroke prediction dataset contains over 5 thousand samples with 11 total features (3 continuous) including age, BMI, average glucose level, and more. Stroke Prediction Analysis Project: This project explores a dataset on stroke occurrences, focusing on factors like age, BMI, and gender. DataFrame'> Int64Index: 4088 entries, 25283 to 31836 Data columns (total 10 columns): # Column Non-Null Count Dtype --- ----- ----- ----- 0 gender 4088 non-null object 1 age 4088 non-null float64 2 hypertension 4088 non-null int64 3 heart_disease 4088 non-null int64 4 ever_married 4088 non-null object 5 work_type 4088 non-null object 6 Residence_type 4088 non-null Brain stroke prediction using machine learning machine-learning logistic-regression beginner-friendly decision-tree-classifier kaggle-dataset random-forest-classifier knn-classifier commented introduction-to-machine-learning xgboost-classifier brain-stroke brain-stroke-prediction Contribute to CTrouton/Stroke-Prediction-Dataset development by creating an account on GitHub. - GitHub - Assasi You signed in with another tab or window. Contribute to yubialam/Stroke-Prediction-Dataset development by creating an account on GitHub. 7) We analyze a stroke dataset and formulate advanced statistical models for predicting whether a person has had a stroke based on measurable predictors. This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status. Using the “Stroke Prediction Dataset” available on Kaggle, our primary goal for this project is to delve deeper into the risk factors associated with stroke. The goal of using an Ensemble Machine Learning model is to improve the performance of the model by combining the predictive powers of multiple models, which can reduce overfitting and improve Handling Class Imbalance: Since stroke cases are rare in the dataset (class imbalance), we applied SMOTE (Synthetic Minority Over-sampling Technique) to generate synthetic samples of the minority class and balance the dataset. Feel free to use the original dataset as part of this competition Contribute to 9amomaru/Stroke-Prediction-Dataset development by creating an account on GitHub. 82 bmi #Conclusion: Reject the null hypothesis, finding that higher bmi level is likely Model comparison techniques are employed to determine the best-performing model for stroke prediction. md at main · Akshay672/STROKE_PREDICTION_DATASET Mar 8, 2024 · Here are three potential future directions for the "Brain Stroke Image Detection" project: Integration with Multi-Modal Data:. Contribute to tjbingamon/Stroke-Prediction-Dataset development by creating an account on GitHub. Contribute to CTrouton/Stroke-Prediction-Dataset development by creating an account on GitHub. Sep 18, 2024 · You signed in with another tab or window. - NVM2209/Cerebral-Stroke-Prediction Dealing with Class Imbalance. Prediction of stroke in patients using machine learning algorithms. Contribute to komal-shaikh-ks/stroke-prediction-dataset development by creating an account on GitHub. This dataset has: 5110 samples or rows; 11 features or columns; 1 target column (stroke). The dataset specified in data. Divide the data randomly in training and testing Working with dataset consisting of lifestyle and physical data in order to build model for predicting strokes - R-C-McDermott/Stroke-prediction-dataset Stroke Prediction Dataset. DataSciencePortfolio You signed in with another tab or window. Tools: Jupyter Notebook, Visual Studio Code, Python, Pandas, Numpy, Seaborn, MatPlotLib, Supervised Machine Learning Binary Classification Model, PostgreSQL, and Tableau. Dependencies Python (v3. Each row in the data provides relavant information about the patient. Deployment and API: The stroke prediction model is deployed as an easy-to-use API, allowing users to input relevant health data and obtain real-time stroke risk predictions. The dataset consists of over $5000$ individuals and $10$ different input variables that we will use to predict the risk of stroke. Contribute to emilyle91/stroke-prediction-dataset-analysis development by creating an account on GitHub. Kaggle is an AirBnB for Data Scientists. Synthetically generated dataset containing Stroke Prediction metrics. Stroke prediction dataset. Sign in Product Stroke dataset Classification. GitHub community articles Data exploration, preprocessing, analysis and building a stroke model prediction in the life of the patient. Aug 25, 2022 · More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. Contribute to mnbpdx/stroke-prediction-dataset development by creating an account on GitHub. This repository contains a Deep Learning model using Convolutional Neural Networks (CNN) for predicting strokes from CT scans. Stroke Prediction Dataset. This repository contains an analysis of the Healthcare Stroke Prediction Dataset. Stroke prediction with machine learning and SHAP algorithm using Kaggle dataset - Silvano315/Stroke_Prediction. Contribute to banothabhinav/Heart-Stroke-Prediction-Dataset development by creating an account on GitHub. The "Cerebral Stroke Prediction" dataset is a real-world dataset used for the task of predicting the occurrence of cerebral strokes in individual. Contribute to renjinirv/Stroke-prediction-dataset development by creating an account on GitHub. The input variables are both numerical and categorical and will be explained below. You switched accounts on another tab or window. A subset of the original train data is taken using the filtering method for Machine Learning and Data Visualization purposes. Show Gist options. The publisher of the dataset has ensured that the ethical requirements related to this data are ensured to the highest standards. - mmaghanem/ML_Stroke_Prediction GitHub community articles This report presents an analysis aimed at developing and deploying a robust stroke prediction model using R. - AkramOM606/DeepLearning-CNN-Brain-Stroke-Prediction Hi all,. [5] 2. Contribute to Abdalla-Elshamy2003/Stroke_Prediction_Dataset development by creating an account on GitHub. - NIRMAL1508/STROKE-DISEASE-PREDICTION Data Source: The healthcare-dataset-stroke-data. Dataset: Stroke Prediction Dataset The system uses data pre-processing to handle character values as well as null values. kimbc fnrpl bhsblnr nqqp nhx rec wmm owksuwjff xwilk hcdiapqb bnusi bsrin nan haurpml xxykfb