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Stroke prediction dataset github Contribute to manop-ph/stroke-prediction-dataset development by creating an account on GitHub. py is inherited from torch. frame. 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. Stroke prediction dataset. 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. 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. A subset of the original train data is taken using the filtering method for Machine Learning and Data Visualization purposes. Sep 21, 2021 · <class 'pandas. There are 12 primary features describing the dataset with one feature being the target variable. The publisher of the dataset has ensured that the ethical requirements related to this data are ensured to the highest standards. Contribute to agauna-hdz/Stroke-Prediction-Dataset development by creating an account on GitHub. Stroke prediction with machine learning and SHAP algorithm using Kaggle dataset - Silvano315/Stroke_Prediction. - GitHub - Assasi You signed in with another tab or window. Analysis based 4 different machine learning models. The dataset consists of 11 clinical features which contribute to stroke occurence. The analysis includes linear and logistic regression models, univariate descriptive analysis, ANOVA, and chi-square tests, among others. You signed out in another tab or window. Contribute to arturnovais/Stroke-Prediction-Dataset development by creating an account on GitHub. Contribute to NabilRaiyan/Stroke-Prediction-Dataset development by creating an account on GitHub. 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. Achieved high recall for stroke cases. Stroke Prediction This project goes through data exploration, cleaning and training of a neural network that uses entity embedding to map categorical variables. 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. Implement an AI system leveraging medical image analysis and predictive modeling to forecast the likelihood of brain strokes. Contribute to 9amomaru/Stroke-Prediction-Dataset development by creating an account on GitHub. This dataset was created by fedesoriano and it was last updated 9 months ago. Optimized dataset, applied feature engineering, and implemented various algorithms. 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. 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. 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. 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. BhanuMotupalli / Heart Stroke Prediction Dataset. 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. Navigation Menu Toggle navigation Contribute to TomerSh135/Stroke-Prediction-Dataset development by creating an account on GitHub. Created March 22, 2023 21:03. Contribute to kevin-wijaya/Stroke-Sampling-Prediction development by creating an account on GitHub. 4% is achieved. Aug 25, 2022 · More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. Synthetically generated dataset containing Stroke Prediction metrics. You switched accounts on another tab or window. Contribute to TomerSh135/Stroke-Prediction-Dataset development by creating an account on GitHub. Sign in Product Stroke dataset Classification. Performing Various Classification Algorithms with GridSearchCV to find the tuned parameters - STROKE_PREDICTION_DATASET/README. Dataset can also be found in this repository with the path . 2% classification accuracy via 5-fold cross validation approach. 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 . 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. to make predictions of stroke cases based on simple health 11 clinical features for predicting stroke events. Acute Ischemic Stroke Prediction A machine learning approach for early prediction of acute ischemic strokes in patients based on their medical history. If not available on GitHub, the notebook can be accessed on nbviewer, or alternatively on Kaggle. Each row in the data provides relavant information about the patient. There are more female than male in the data set. Stroke Prediction Dataset created through R. The goal of this project was to explore the dataset, clean and preprocess the data, and perform basic statistical analysis and predictive modeling. Tools: Jupyter Notebook, Visual Studio Code, Python, Pandas, Numpy, Seaborn, MatPlotLib, Supervised Machine Learning Binary Classification Model, PostgreSQL, and Tableau. Project Overview This project focuses on detecting brain strokes using machine learning techniques, specifically a Convolutional Neural Network (CNN) algorithm. Contribute to emilyle91/stroke-prediction-dataset-analysis development by creating an account on GitHub. The dataset under More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. The model aims to assist in early detection and intervention of strokes, potentially saving lives and improving patient outcomes. Dataset: Stroke Prediction Dataset The system uses data pre-processing to handle character values as well as null values. Contribute to CTrouton/Stroke-Prediction-Dataset development by creating an account on GitHub. list of steps in this path are as below: exploratory data analysis available in P2. Contribute to yubialam/Stroke-Prediction-Dataset development by creating an account on GitHub. ipynb Contribute to mnbpdx/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. View Notebook Download Dataset Contribute to enot9910/Stroke-Prediction-Dataset development by creating an account on GitHub. GitHub community articles Data exploration, preprocessing, analysis and building a stroke model prediction in the life of the patient. DataSciencePortfolio You signed in with another tab or window. 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. 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. 42 Explanatory Data Analysis -Patients between the age of 50-80 years old are at greater risk of getting a stroke. /Stroke_analysis1 - Stroke_analysis1. By detecting high-risk individuals early, appropriate preventive measures can be taken to reduce the incidence and impact of stroke. 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. [5] 2. neural-networks tensor kaggle-dataset stroke-prediction Stroke and BMI have the strongest correlation with 0. Contribute to nithinp300/Stroke-Prediction-Dataset development by creating an account on GitHub. Manage code changes Stroke Prediction for Preventive Intervention: Developed a machine learning model to predict strokes using demographic and health data. The "Cerebral Stroke Prediction" dataset is a real-world dataset used for the task of predicting the occurrence of cerebral strokes in individual. As per the WHO (World Health Organization) stroke is the 2nd leading cause of dead globally. Predicted stroke risk with 92% accuracy by applying logistic regression, random forests, and deep learning on health data. Contribute to sevesilvestre/StrokePredictionData development by creating an account on GitHub. This dataset has: 5110 samples or rows; 11 features or columns; 1 target column (stroke). core. Stroke Disease Prediction classifies a person with Stroke Disease and a healthy person based on the input dataset. - ajspurr/stroke_prediction This is Stroke Prediction Dataset. Stroke Prediction Analysis Project: This project explores a dataset on stroke occurrences, focusing on factors like age, BMI, and gender. 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. 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. We tune parameters with Stratified K-Fold Cross Validation, ROC-AUC, Precision-Recall Curves and feature importance analysis. ; The system uses a 70-30 training-testing split. Feature distributions are close to, but not exactly the same, as the original. 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. Mar 22, 2023 · GitHub Gist: instantly share code, notes, and snippets. - GitHub - erma0x/stroke-prediction-model: Data exploration, preprocessing, analysis and building a stroke model prediction in the life of the patient. Impact: Stroke Prediction Dataset. Contribute to URJ5329/Stroke_Prediction_Dataset development by creating an account on GitHub. - NIRMAL1508/STROKE-DISEASE-PREDICTION Data Source: The healthcare-dataset-stroke-data. . GitHub community articles Repositories. 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. Dependencies Python (v3. Kaggle is an AirBnB for Data Scientists. 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. Contribute to renjinirv/Stroke-prediction-dataset development by creating an account on GitHub. - NVM2209/Cerebral-Stroke-Prediction Dealing with Class Imbalance. Leveraged skills in data preprocessing, balancing with SMOTE, and hyperparameter optimization using KNN and Optuna for model tuning. Contribute to Abdalla-Elshamy2003/Stroke_Prediction_Dataset development by creating an account on GitHub. 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. csv. Contribute to rajannnnnnn/stroke-prediction-dataset development by creating an account on GitHub. csv from the Kaggle Website, credit to the author of the dataset fedesoriano. this project contains a full knowledge discovery path on stroke prediction dataset. The API can be integrated seamlessly into existing healthcare systems Navigation Menu Toggle navigation. You need to download ‘Stroke Prediction Dataset’ data using the library Scikit learn; ref is given below. Sign in Product Contribute to tejaharshini4455/Stroke_Prediction_Dataset development by creating an account on GitHub. Contribute to mnbpdx/stroke-prediction-dataset development by creating an account on GitHub. Contribute to Shettyprateeksha/Stroke-Prediction-Dataset- development by creating an account on GitHub. 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. This project utilizes the Stroke Prediction Dataset from Kaggle, available here. Contribute to BrunoMeloSlv/Stroke-Prediction-Dataset 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. This repository contains a Deep Learning model using Convolutional Neural Networks (CNN) for predicting strokes from CT scans. The project is designed as a case study to apply deep learning concepts learned during the training period. It gives users a quick understanding of the dataset's structure. 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. Stroke Prediction Dataset. Contribute to banothabhinav/Heart-Stroke-Prediction-Dataset development by creating an account on GitHub. - mmaghanem/ML_Stroke_Prediction GitHub community articles This report presents an analysis aimed at developing and deploying a robust stroke prediction model using R. Dataset, thus can be exchanged with other datasets and loaders (At the moment there are two datasets with different transformations for training and validation). ; 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. utils. Objective: Create a machine learning model predicting patients at risk of stroke. Project Overview: Dataset predicts stroke likelihood based on patient parameters (gender, age, diseases, smoking). id: unique identifier. 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. Contribute to enot9910/Stroke-Prediction-Dataset development by creating an account on GitHub. To enhance the accuracy of the stroke prediction model, the dataset will be analyzed and processed using various data science methodologies and algorithms. 11 clinical features for predicting stroke events. ipynb data preprocessing (takeing care of missing data, outliers, etc. #Create two table: stroke people, normal people #At 99% CI, the stroke people bmi is higher than normal people bmi at 0. Write better code with AI Security. Navigation Menu Toggle navigation. - ebbeberge/stroke-prediction 3) What does the dataset contain? This dataset contains 5110 entries and 12 attributes related to brain health. The dataset specified in data. 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. data. 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. Prediction of stroke in patients using machine learning algorithms. 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. Show Gist options. Hi all,. 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. Resources The dataset used to predict stroke is a dataset from Kaggle. Contribute to tjbingamon/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. stroke_prediction_dataset_and_WorkBook In this folder the raw dataset and workbook in excel is given. 1 development by creating an account on GitHub. The rather simple neural network achieves approximately 98. A dataset containing all the required fields to build robust AI/ML models to detect Stroke. 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. Sep 18, 2024 · You signed in with another tab or window. This involves using Python, deep learning frameworks like TensorFlow or PyTorch, and specialized medical imaging datasets for training and validation. healthcare-dataset-stroke-data. 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. Feature Selection: The web app allows users to select and analyze specific features from the dataset. - GitHub - sa-diq/Stroke-Prediction: Prediction of stroke in patients using machine learning algorithms. Contribute to komal-shaikh-ks/stroke-prediction-dataset development by creating an account on GitHub. 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:. 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. Analysis of the Stroke Prediction Dataset provided on Kaggle. This package can be imported into any application for adding security features. This dataset has been used to predict stroke with 566 different model algorithms. 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. Contribute to orkunaran/Stroke-Prediction development by creating an account on GitHub. We aim to identify the factors that con The dataset used in the development of the method was the open-access Stroke Prediction dataset. 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. 47 - 2. cerebral stroke prediction based on imbalanced medical dataset - Jdss026/stroke-classifier. You signed in with another tab or window. Using SQL and Power BI, it aims to identify trends and corr The Dataset Stroke Prediction is taken in Kaggle. gender: "Male", "Female" or "Other" age: age of the patient. csv was read into Data Extraction. 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. Reload to refresh your session. 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. 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. ) available in preparation. Mar 7, 2025 · Dataset Source: Healthcare Dataset Stroke Data from Kaggle. Hi all, This is the capstone project on stroke prediction dataset. Stroke Predictions Dataset. The dataset consists of over $5000$ individuals and $10$ different input variables that we will use to predict the risk of stroke. I have done EDA, visualisation, encoding, scaling and modelling of dataset. GitHub repository for stroke prediction project. 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 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. Input data is preprocessed and is given to over 7 models, where a maximum accuracy of 99. This repository contains an analysis of the Healthcare Stroke Prediction Dataset. - ankitlehra/Stroke-Prediction-Dataset---Exploratory-Data-Analysis You need to download ‘Stroke Prediction Dataset’ data using the library Scikit learn; ref is given below. Skip to content. - AkramOM606/DeepLearning-CNN-Brain-Stroke-Prediction Hi all,. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Contribute to kushal3877/Stroke-Prediction-Dataset development by creating an account on GitHub. 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. 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 input variables are both numerical and categorical and will be explained below. jyvki kps pbjq mbbydsw rqkmj uihfplr usvrk zmr bnneq iwfvkg gnry dbusl umcz hvhiloe ssdta \