Lung Disease Detection

Respiratory Disorder Classification Based on Lung Auscultation Sounds.

This project uses machine learning and deep learning techniques to classify respiratory disorders from lung auscultation audio recordings. It also includes a chatbot system for assisting doctors with patient-related queries.

Features

• Respiratory disease prediction using lung sounds
• Audio waveform and spectrogram analysis
• Flask-based web application
• RAG chatbot for doctor assistance
• PDF report generation
• Deep learning models using TensorFlow/Keras

---

Dataset

Respiratory Sound Database:

https://www.kaggle.com/vbookshelf/respiratory-sound-database

The dataset contains:

• 920 annotated recordings
• 126 patients
• Crackles and wheezes detection
• Multiple respiratory disorder classes

---

Technologies Used

• Python
• Flask
• TensorFlow/Keras
• Librosa
• NumPy
• Scikit-learn
• HTML/CSS

---

Installation

Clone repository:

git clone https://github.com/Nithin7king/lung_disease_detection.git