Github Dubeyvaishali001 Heart Attack Prediction

Github Omarmakkeyah Heart Attack Prediction Contribute to dubeyvaishali001 heart attack prediction development by creating an account on github. A web application that predicts the likelihood of a heart attack based on user inputs using machine learning and shap for explainability. built with python (flask), html css, and deployed online for public access.

Github Farisjamaan Heart Attack Prediction A Machine Learning Model This project aims to predict the likelihood of a heart attack based on various health indicators using machine learning techniques. the dataset used contains patient data with features such as age, cholesterol levels, blood pressure, and more. Github gist: instantly share code, notes, and snippets. The goal is to predict if a person has a high risk of heart attack based on the information provided. the dataset is already cleaned and ready to be used for analysis and prediction. Discover what actually works in ai. join millions of builders, researchers, and labs evaluating agents, models, and frontier technology through crowdsourced benchmarks, competitions, and hackathons.

Github Sasank1947 Heart Attack Prediction Heart Attack Predictor The goal is to predict if a person has a high risk of heart attack based on the information provided. the dataset is already cleaned and ready to be used for analysis and prediction. Discover what actually works in ai. join millions of builders, researchers, and labs evaluating agents, models, and frontier technology through crowdsourced benchmarks, competitions, and hackathons. Contribute to dubeyvaishali001 heart attack prediction development by creating an account on github. This project predicts the risk of a heart attack using machine learning models based on a dataset containing various medical and demographic factors. the model is trained using a classification algorithm (xgboost) and deployed via a flask web application. This project aims to predict heart attack risk using a dataset of 303 patient records with 14 clinical features, including age, sex, chest pain type (cp), resting blood pressure (trtbps), cholesterol (chol), and maximum heart rate (thalachh). Objectives: the primary goal of this project is to predict the probability of a person having a heart attack based on their gender, age, and cholesterol level using a linear model as the baseline model, a logistic model, and a random forest model.

Github Mahsabakhtiari Heart Attack Prediction Cnn Heart Attack Contribute to dubeyvaishali001 heart attack prediction development by creating an account on github. This project predicts the risk of a heart attack using machine learning models based on a dataset containing various medical and demographic factors. the model is trained using a classification algorithm (xgboost) and deployed via a flask web application. This project aims to predict heart attack risk using a dataset of 303 patient records with 14 clinical features, including age, sex, chest pain type (cp), resting blood pressure (trtbps), cholesterol (chol), and maximum heart rate (thalachh). Objectives: the primary goal of this project is to predict the probability of a person having a heart attack based on their gender, age, and cholesterol level using a linear model as the baseline model, a logistic model, and a random forest model.