Cystic Fibrosis (CF) is a genetic disorder that severely affects the lungs and digestive organs. Timely identification of the disease can significantly enhance treatment effectiveness and patient survival. This work introduces a deep learning-based framework that utilizes Convolutional Neural Networks (CNN) to identify early signs of Cystic Fibrosis from medical images and clinical indicators. The proposed model automatically extracts discriminative features and performs classification between CF and non-CF cases. Experimental findings demonstrate strong performance and reliability, highlighting the usefulness of artificial intelligence in supporting early clinical diagnosis and healthcare decision systems.
Mr. S. Kumaravel (Thu,) studied this question.