Gastric cancer (GC) is one of the most serious health problems worldwide. Chronic atrophic gastritis (CAG) is most commonly caused by Helicobacter pylori (H. pylori) infection. Currently, endoscopic detection of early gastric cancer (EGC) and CAG remains challenging for endoscopists, and the diagnostic accuracy of H. pylori infection by endoscopy is approximately 70%. Artificial intelligence (AI) can assist endoscopic diagnosis including detection, prediction of depth of invasion, boundary delineation, and anatomical location of EGC, and has achievable diagnostic ability even comparable to experienced endoscopists. In this review we summarized various AI-assisted systems in the diagnosis of EGC, CAG, and H. pylori infection.
Keyphrases
- artificial intelligence
- helicobacter pylori
- helicobacter pylori infection
- machine learning
- big data
- deep learning
- ultrasound guided
- mental health
- healthcare
- public health
- loop mediated isothermal amplification
- mass spectrometry
- cell migration
- climate change
- optical coherence tomography
- social media
- high resolution
- health information