DETECTION OF CANCEROUS CELLS IN LUNGS USING MACHINE LEARNING

Abstract

Lung cancer is a devastating disease that continues to pose a significant threat to public health worldwide. Despite advances in medical technology, early detection and effective treatment remain essential to improving survival rates. Medical professionals often rely on computed tomography (CT) scans for imaging, but interpreting and identifying cancerous cells can prove challenging even for experienced physicians. Consequently, computer-aided diagnosis (CAD) has emerged as a promising tool for enhancing diagnostic accuracy in lung cancer cases.