Artificial Intelligence in Gastrointestinal Endoscopy
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Artificial intelligence (AI) is rapidly integrating into modern technology and clinical practice. Although in its nascency, AI has becomea hot topic of investigation for applications in clinical practice. Multiple fields of medicine have embraced the possibility of a future withAI assisting in diagnosis and pathology applications. In the field of gastroenterology, AI has been studied as a tool to assist in risk stratification, diagnosis, and pathologic identification. Specifically, AI has become of great interest in endoscopy as a technology with substantial potential to revolutionize the practice ofa modern gastroenterologist. From cancer screening to automated report generation, AI has touched upon all aspects of modernendoscopy. Here, we review landmark AI developments in endoscopy. Starting with broad definitions to develop understanding, we will summarizethe current state of AI research and its potential applications. With innovation developing rapidly, this article touches upon theremarkable advances in AI-assisted endoscopy since its initial evaluation at the turn of the millennium, and the potential impact theseAI models may have on the modern clinical practice. As with any discussion of new technology, its limitations must also be understoodto apply clinical AI tools successfully.
Abstract
Artificial intelligence (AI) is rapidly integrating into modern technology and clinical practice. Although in its nascency, AI has becomea hot topic of investigation for applications in clinical practice. Multiple fields of medicine have embraced the possibility of a future withAI assisting in diagnosis and pathology applications. In the field of gastroenterology, AI has been studied as a tool to assist in risk stratification, diagnosis, and pathologic identification. Specifically, AI has become of great interest in endoscopy as a technology with substantial potential to revolutionize the practice ofa modern gastroenterologist. From cancer screening to automated report generation, AI has touched upon all aspects of modernendoscopy. Here, we review landmark AI developments in endoscopy. Starting with broad definitions to develop understanding, we will summarizethe current state of AI research and its potential applications. With innovation developing rapidly, this article touches upon theremarkable advances in AI-assisted endoscopy since its initial evaluation at the turn of the millennium, and the potential impact theseAI models may have on the modern clinical practice. As with any discussion of new technology, its limitations must also be understoodto apply clinical AI tools successfully.
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