A COMPREHENSIVE REVIEW OF GASTROINTESTINAL CANCER: FROM PATHOGENESIS TO COMPUTATIONAL DIAGNOSIS

Gastrointestinal (GI) cancers, which include a broad spectrum of malignant
conditions affecting the digestive system and related organs, continue to
rank among the leading causes of cancer-related mortality globally.
Although early identification and precise diagnosis are crucial for improving
patient survival, clinical detection remains challenging, as these malignancies are
frequently diagnosed at advanced stages. This paper consolidates current
knowledge on the mechanisms underlying GI cancer development, reviews both
established and emerging screening and diagnostic techniques, and critically
examines the role of computational approaches including artificial intelligence,
machine learning, and deep learning in enhancing diagnostic accuracy. In addition,
the relative effectiveness of various screening modalities is systematically compared,
and strategic recommendations are proposed for integrating advanced
computational technologies to achieve more efficient and reliable GI cancer
detection.