EARLY DETECTION AND PREVENTION OF RESPIRATORY DISEASES AMONG RESIDENTS OF INDUSTRIAL AREAS THROUGH RADIOLOGICAL IMAGE ANALYSIS

Environmental pollution caused by industrial activities has a profound impact on respiratory health, particularly among populations living in close proximity to industrial zones. This thesis explores the role of artificial intelligence (AI)-based radiological image analysis, particularly chest X-rays, in the early detection and prevention of respiratory diseases in these vulnerable populations. By applying convolutional neural networks (CNNs) to chest radiographs, the study aims to identify early pathological signs of diseases such as chronic bronchitis, pneumoconiosis, and early-stage pneumonia, which are commonly observed in industrial environments.