This study combines artificial intelligence with tongue images, by collating and collecting tongue images and diagnostic and pathological results of gastroscopic diseases, mining and analysing the correlation between tongue images and OLGA, OLGIM stages, Correa sequences and constructing prediction models, to deeply investigate the relationship between tongue images and precancerous diseases, precancerous lesions and gastric cancer.

Firstly, tongue pictures and patient information will be collected after the patient signed an informed consent form.

Secondly, after the patient undergoes gastroscopy, patient gastroscopy reports and pathology reports will be obtained.

Thirdly, the investigator will assess the patient's gastroscopy report for the Correa sequence of gastric cancer with OLGA and OLGIM staging.

Finally, the patient's tongue image, information and gastric cancer cascade response are matched to construct an artificial intelligence model and assess the quality of the model.

Inclusion Criteria:

• Patients between 40 and 80 years of age who are scheduled for gastroscopy.
• Patients all gave their informed consent and signed the informed consent form.

Exclusion Criteria:

• Persons with severe cardiac, cerebral, pulmonary or renal dysfunction or psychiatric disorders who are unable to participate in gastroscopy.
• Patients with previous surgical procedures on the gastrointestinal tract.
• Patients taking bismuth or other staining drugs.

Patients aged 40-80 years who will undergo gastroscopy and fulfil the inclusion criteria who do not meet the exclusion criteria.