Emerging molecules, tools, technology, and future of surgical knife in gastroenterology

Table 1 Some of the applications of machine learning in gastroenterology[49]

Modality	Clinical presentation/ diagnosis	Application
Upper GI endoscopy	Barrett’s oesophagus	Identification of early cancerous lesion; target site for biopsy; endoscopic assistance
	Oesophageal cancer	In the diagnosis of SCC
	H. pylori infection	Atrophy vs metaplasia
	Gastric cancer	Tumor vs non tumorous tissue; depth of invasion
Capsule endoscopy	GI bleed	Source of bleed; detecting pathologic lesions such as erosions and ulcers
	Celiac	Finding villous atrophy
Colonoscopy	Colorectal cancer	Bowel preparation assessment; adenoma detection; assistance
	Ulcerative colitis	Severity and relapses
Ultrasound-based test-fibro scan/elastography	Various liver diseases; benign & malignant	Fibrosis stage
	Pancreatic diseases	Tumour assessment, degree of intrapancreatic fat
	GI pathology	Survival prediction in colorectal cancer; identification of MSI; HCC vs cholangiocarcinoma; predict prognosis and survival in HCC

GI: Gastrointestinal; SCC: Squamous cell carcinoma; H. Pylori: Helicobacter pylori; HCC: Hepatocellular carcinoma.