ASGE International Sampler (On-Demand)-Why Machine Learning in Gastroenterology

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The document discusses the application of Artificial Intelligence (AI) in Gastroenterology, particularly in gastrointestinal (GI) health care. AI, including machine learning and deep learning, is increasingly being used to improve clinical practice quality in imaged-based specialties like endoscopy. The main objectives include addressing clinical challenges faced by gastroenterologists, such as colon polyp detection, Barrett's esophagus, gastric cancer, and small bowel disease. AI aims to enhance outcomes, decrease healthcare delivery variances, and lower medical costs by improving diagnostic accuracy and patient outcomes.<br /><br />Studies have shown that AI applications in GI endoscopy, such as colonoscopy, can significantly improve adenoma detection rate (ADR) without increasing withdrawal time. AI systems like CADe/ CADx have been developed for colon polyp detection and characterization. Additionally, AI has been applied to improve the surveillance of conditions like Barrett's esophagus and gastric cancer by aiding in dysplasia and cancer differentiation. Moreover, AI has enhanced reading speeds and sensitivity in capsule endoscopy, leading to significant time savings and improved lesion detection accuracy.<br /><br />The adoption of AI in GI is essential due to its potential to bridge skill gaps among endoscopists and improve patient outcomes in conditions like colon cancer prevention and upper GI bleeding. By leveraging AI technology, GI healthcare providers can benefit from increased diagnostic accuracy, reduced healthcare costs, and enhanced workflow efficiency. Overall, the document emphasizes the importance and benefits of incorporating AI into Gastroenterology to advance patient care and outcomes in the field.

Asset Subtitle

Seth A. Gross, MD, FACG, FASGE, AGAF

Meta Tag

Concept Artificial Intelligence

Concept Endoscopy

Concept Machine Learning

Concept Deep learning

Concept Lower Endoscopy

Keywords

Artificial Intelligence

Gastroenterology

GI healthcare

machine learning

deep learning

endoscopy

colon polyp detection

Barrett's esophagus

gastric cancer

capsule endoscopy

Artificial Intelligence

Endoscopy

Machine Learning

Deep learning

Lower Endoscopy