Pneumonia Classification | Telegram Bot | Build CNN Model in PyTorch
🫁 Pneumonia Classification Telegram Bot using Custom CNN | Deep Learning & Telegram Bot Integration
📌 Overview
In this video, we showcase a real-time Pneumonia Classification Telegram Bot built using a custom CNN model in PyTorch. The bot allows users to send chest X-ray images via Telegram, and it responds with the predicted class — Pneumonia or Normal — along with the confidence score.
Whether you're a medical AI enthusiast, a deep learning practitioner, or someone exploring Telegram bots, this project is an excellent demonstration of combining image classification with real-time messaging platforms.
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🔧 Key Features:
✅ Custom CNN for X-ray classification
✅ PyTorch-powered inference pipeline
✅ Telegram Bot integration using `python-telegram-bot`
✅ Predicts and sends back class label + confidence
✅ Clean and modular codebase
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📂 GitHub Repository
🔗 https://github.com/NitinCVOrbit/Pneum...
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🧠 Model Architecture Summary
5 convolutional layers with ReLU, BatchNorm, and MaxPooling
3 fully connected layers with BatchNorm
Final output layer with Softmax (2 classes: Pneumonia, Normal)
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💬 Drop a comment if you'd like a tutorial on how to deploy this bot on cloud platforms like Heroku or Railway!
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