Artificial intelligence in gastric cancer: a systematic review.

OBJECTIVE

This study aims to systematically review the application of artificial intelligence (AI) techniques in gastric cancer and to discuss the potential limitations and future directions of AI in gastric cancer.

METHODS

A systematic review was performed that follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Pubmed, EMBASE, the Web of Science, and the Cochrane Library were used to search for gastric cancer publications with an emphasis on AI that were published up to June 2020. The terms "artificial intelligence" and "gastric cancer" were used to search for the publications.

RESULTS

A total of 64 articles were included in this review. In gastric cancer, AI is mainly used for molecular bio-information analysis, endoscopic detection for Helicobacter pylori infection, chronic atrophic gastritis, early gastric cancer, invasion depth, and pathology recognition. AI may also be used to establish predictive models for evaluating lymph node metastasis, response to drug treatments, and prognosis. In addition, AI can be used for surgical training, skill assessment, and surgery guidance.

CONCLUSIONS

In the foreseeable future, AI applications can play an important role in gastric cancer management in the era of precision medicine.