• Sanket Kamble

Pneumonia is a serious health issue worldwide, especially in areas with limited medical resources. Diagnosing pneumonia from chest X-rays requires expertise and can take time. This project uses artificial intelligence (AI) and machine learning (ML), specifically convolutional neural networks (CNNs), to help detect pneumonia automatically from X-ray images. By training the CNN model on a large set of X-ray images, it learns to recognize patterns associated with pneumonia. Advanced techniques were used to improve accuracy and make the model reliable across different types of X-rays. Our results show that AI can quickly identify possible pneumonia cases, helping doctors start treatment sooner. This approach has the potential to make pneumonia diagnosis faster and more accessible, especially in regions that need it most.

Machine Learning, Deep Learning,Big Data Analytics.

"Detection of Pneumonia in Chest X-rays using CNN based image processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.i112-i115, May-2025, Available :http://www.jetir.org/papers/JETIR2505912.pdf

"Detection of Pneumonia in Chest X-rays using CNN based image processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppi112-i115, May-2025, Available at : http://www.jetir.org/papers/JETIR2505912.pdf