AI-Powered Endoscopic Image Classification: CNN-Based Gastric Cancer and Ulcer Detection
doi:10.9718/JBER.2020.41.2.101 Introduction Gastric cancer remains one of the most lethal malignancies worldwide, ranking among the top causes of cancer-related mortality. Despite advances in screening, early detection of gastric cancer is still challenging , particularly due to the morphological similarities between benign gastric ulcers and early gastric cancers . This diagnostic ambiguity often leads to misclassification, delayed treatment, and poorer clinical outcomes. Traditional gastroscopy, though regarded as the gold standard, has limitations. Outcomes depend heavily on the skill, fatigue level, and interpretive ability of the endoscopist . In fact, studies reveal that up to 11.3% of upper gastrointestinal cancers may be missed during endoscopy . Given these limitations, the application of Artificial Intelligence (AI) and specifically Convolutional Neural Networks (CNNs) , offers a transformative approach in Computer-Aided Diagnosis (CAD) . This column delves into a recen...