Generative AI in the Categorisation of Paediatric Pneumonia on Chest Radiographs

Apply

Generative AI in the Categorisation of Paediatric Pneumonia on Chest Radiographs

Journal Title: International Journal of Current Science Research and Review - Year 2025, Vol 8, Issue 02

Abstract

Paediatric pneumonia is a leading cause of morbidity and mortality worldwide, necessitating accurate and timely diagnosis. This study explores the application of Generative AI for categorising paediatric pneumonia using chest radiographs. Leveraging deep learning techniques, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), we enhance image quality, generate synthetic training data, and improve model generalizability. The proposed framework integrates AI-driven feature extraction, convolutional neural networks (CNNs), and attention mechanisms to improve diagnostic accuracy. The results demonstrate significant improvements in classification performance compared to traditional methods, with a focus on interpretability and clinical usability.

Authors and Affiliations

Santosh Kumar

Keywords

Chest Radiographs Convolutional Neural Networks (CNN) Data Augmentation Deep learning Generative Adversarial Networks (GAN) Generative AI Medical Image Classification Paediatric Pneumonia Pneumonia Diagnosis Synthetic Data.

EP ID EP758947
DOI 10.47191/ijcsrr/V8-i2-16
Views 32
Downloads 0