Pathology for gastrointestinal and hepatobiliary cancers using artificial intelligence
Abstract
From visual data, artificial intelligence (AI) can extract complicated information. Histopathology pictures of gastrointestinal (GI) and liver cancer provide a large quantity of data that human observers can only decipher in part. AI permits the in-depth study of digitized histological slides of GI and liver cancer, complementing human observers, and has a wide variety of clinically useful applications. First, AI can recognize tumor tissue automatically, alleviating pathologists' ever-increasing labor. Furthermore, AI can capture prognostically significant tissue characteristics and so predict clinical prognosis across GI and liver cancer types, perhaps surpassing pathologists' capabilities.
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