{"id":26406509,"url":"https://github.com/whatyuupratama/aodycardio","last_synced_at":"2025-10-15T23:34:59.700Z","repository":{"id":269947254,"uuid":"908928135","full_name":"whatyuupratama/aodycardio","owner":"whatyuupratama","description":null,"archived":false,"fork":false,"pushed_at":"2024-12-27T10:27:08.000Z","size":8,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-01T15:32:14.789Z","etag":null,"topics":["classification","flask"],"latest_commit_sha":null,"homepage":"https://cardiocare.up.railway.app/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/whatyuupratama.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-12-27T10:09:36.000Z","updated_at":"2024-12-27T23:49:05.000Z","dependencies_parsed_at":"2024-12-27T11:25:43.607Z","dependency_job_id":"33204b1c-e109-42fe-9ee6-9610a42068e4","html_url":"https://github.com/whatyuupratama/aodycardio","commit_stats":null,"previous_names":["wahyupratamaaa/c","whatyuupratama/aodycardio"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/whatyuupratama%2Faodycardio","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/whatyuupratama%2Faodycardio/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/whatyuupratama%2Faodycardio/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/whatyuupratama%2Faodycardio/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/whatyuupratama","download_url":"https://codeload.github.com/whatyuupratama/aodycardio/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244075622,"owners_count":20393980,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["classification","flask"],"created_at":"2025-03-17T17:20:03.506Z","updated_at":"2025-10-15T23:34:54.668Z","avatar_url":"https://github.com/whatyuupratama.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# **CardioCare ❤️ AI-Powered Website**\n\n## **⚠️ Important Warning**\nThis project **focuses on integrating AI into the web** to provide an initial overview of **heart disease risks**.  \n\n**The AI predictions provided are not for medical reference!**\n- **CardioCare is not a medical diagnostic tool.**\n- **The predictions shown are based solely on the AI model and the data entered by the user.**\n- **Please consult your doctor or a healthcare professional for accurate diagnosis and treatment.**\n---\n\n## **Project Goals 🎯**\nTo provide health education and an initial overview of heart disease risks by integrating AI technology into an easy-to-use web platform.\n\n## **About the Project 📋**\n**CardioCare** is an interactive landing page that helps users:\n- **Learn about heart disease education** through informative content.\n- **Check their heart health risk** using **AI** trained with **Scikit-Learn**.\n\nThis project combines **AI technology** and **modern web** to create an interactive and user-friendly experience.\n\n---\n\n## **Key Features ✨**\n1. **Heart Disease Education**  \n   Complete and easy-to-understand information about heart disease risks.\n2. **Heart Disease Risk Check**  \n   - Users fill out a simple form (age, blood pressure, cholesterol, etc.).\n   - The Flask backend runs the AI model to predict the health risk.\n   - The result, showing the **initial risk**, is displayed on the ReactJS frontend.\n\n---\n\n## **Technologies Used 🛠️**\n### **Frontend**\n1. ReactJS: Building the interactive user interface.\n2. Axios: Connecting the React frontend with the Flask backend.\n3. TailwindCSS: Modern and responsive styling.\n4. Framer Motion: Make any design animated.\n### **Backend**\n1. Flask: To create the API that receives data from the user and processes the AI model.\n2. Scikit-Learn: Training and running the heart disease risk prediction model.\n3. Pickle: Storing the trained AI model for future use.\n\n---\n\n# API Documentation 📄\n## Endpoint: `/predict`\n**Method:** `POST`  \n**Description:**  \nThis endpoint is used to send user data and receive a prediction regarding the heart disease risk based on the provided input.\n\n---\n\n### Required Data (Request Body)\nThe following data must be sent in JSON format:\n\n| **Parameter**   | **Data Type** | **Description**                                           |\n|-----------------|---------------|---------------------------------------------------------|\n| `age`           | `float`       | User's age (e.g., `45.0`)                                 |\n| `sex`           | `int`         | Gender (1 = Male, 0 = Female)                            |\n| `cp`            | `int`         | Chest pain type (using category numbers)                 |\n| `trestbps`      | `float`       | Resting blood pressure (e.g., `130.0`)                   |\n| `chol`          | `float`       | Cholesterol level (e.g., `250.0`)                        |\n| `fbs`           | `int`         | Fasting blood sugar (1 = \u003e120 mg/dL, 0 = ≤120 mg/dL)     |\n| `restecg`       | `int`         | Resting electrocardiographic results (category number)   |\n| `thalach`       | `float`       | Maximum heart rate during physical activity              |\n| `exang`         | `int`         | Exercise-induced chest pain (1 = Yes, 0 = No)            |\n| `oldpeak`       | `float`       | ST depression during exercise test (e.g., `1.2`)        |\n| `slope`         | `int`         | Slope of the peak exercise ST segment (category number) |\n| `ca`            | `int`         | Number of major vessels colored by fluoroscopy           |\n| `thal`          | `int`         | History of thalassemia (category number)                |\n\nOnce the data is submitted, the server will return a response in JSON format containing the prediction result and suggestions for further steps.\n\n#### Response Structure:\n```json\n{\n  \"prediction\": \"Heart Disease Detected\",\n  \"suggestion\": \"We recommend consulting a doctor for further evaluation.\"\n}\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwhatyuupratama%2Faodycardio","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwhatyuupratama%2Faodycardio","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwhatyuupratama%2Faodycardio/lists"}