🩺 Predictive Pulse: Harnessing Machine Learning for Blood Pressure Analysis

A Flask-based web application that predicts a person's blood pressure stage (e.g., Normal, Hypertension Stage 1/2, Crisis) based on basic health inputs, using a trained ML model. The app also allows users to download the results as a PDF report.

---

🔍 Project Overview

Predictive Pulse is a machine learning project that helps estimate a user's blood pressure category from clinical features like age group, gender, systolic & diastolic BP, and other symptoms.

Key Features:

• Interactive web UI using Flask + HTML/CSS (Bootstrap)
• Trained SVM-based ML model for BP classification
• Client-side PDF generation using jsPDF
• Clean and responsive design
• Lightweight and easy to deploy

---

🧠 How It Works

1. User visits the homepage and enters basic medical inputs through a form.
2. Model predicts the blood pressure stage (e.g., Normal, Crisis).
3. Advice is shown based on the prediction.
4. Download button allows saving the result as a PDF report.

---

🚀 Tech Stack

• Frontend: HTML, CSS (Bootstrap), JavaScript (jsPDF)
• Backend: Python, Flask
• ML Model: Scikit-learn (SVM pipeline)
• Data Processing: Pandas, NumPy
• PDF Generator: jsPDF (client-side)

---

⚙️ Setup Instructions

1. Clone the repository

   git clone https://github.com/your-username/predictive-pulse.git
   cd predictive-pulse
   
   

2. (Optional but Recommended) Create a virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate

3. Install dependencies pip install -r requirements.txt

4. Run the app python app.py

5. Open the app in your browser Navigate to: http://127.0.0.1:5000

---

🧠 Dashboard View

📈 Pulse Prediction Result

🖼️ Screens: Pulse Prediction Tool

⚙️ Model Prediction Output PDF

📘 Prediction Result Report