ReviewFrontiers in medicine2022
The Feasibility of Applying Artificial Intelligence to Gastrointestinal Endoscopy to Improve the Detection Rate of Early Gastric Cancer Screening.
Review in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Artificial intelligence in endoscopy and colonoscopy: a comprehensive bibliometric analysis of global research trends.Frontiers in medicine · 2025Pooled it
- Prognostic factors for overall survival in patients with early gastric cancer: a retrospective cohort study based on SEER database.Journal of gastrointestinal oncology · 2025Article
- Integrated bioinformatic and machine learning analysis identifies MCM7 and ADAM17 as potential biomarkers for early stage gastric cancer.Journal of gastrointestinal oncology · 2025Article
- Role of artificial intelligence in screening and medical imaging of precancerous gastric diseases.World journal of clinical oncology · 2025Review
- Article
- Comparative analysis of gastric cancer risk attribution (1990-2021) and 2050 burden projection in China, Japan, and South Korea: an age-period-cohort modeling approach based on the Global Burden of Disease 2021 study.Frontiers in oncology · 2025Article
- Functional Role of miR-499a-5p in the Development of Gastric Cancer.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2024Article
- Endoscopic Diagnosis of Early Gastric Cancer and High-Risk Gastritis.The Korean journal of helicobacter and upper gastrointestinal research · 2024Review
- Predictive efficacy of combined tumor markers and gastrin for recurrence after endoscopic submucosal dissection in early gastric cancer patients.American journal of translational research · 2024Article
- Prognostic Value and Potential Regulatory Mechanism of H19 in Stomach Adenocarcinoma.Journal of oncology · 2022Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Convolutional neural networks in the field of artificial intelligence show great potential in image recognition. It assisted endoscopy to improve the detection rate of early gastric cancer. The 5-year survival rate for advanced gastric cancer is less than 30%, while the 5-year survival rate for early gastric cancer is more than 90%. Therefore, earlier screening for gastric cancer can lead to a better prognosis. However, the detection rate of early gastric cancer in China has been extremely low due to many factors, such as the presence of gastric cancer without obvious symptoms, difficulty identifying lesions by the naked eye, and a lack of experience among endoscopists. The introduction of artificial intelligence can help mitigate these shortcomings and greatly improve the accuracy of screening. According to relevant reports, the sensitivity and accuracy of artificial intelligence trained on deep cirrocumulus neural networks are better than those of endoscopists, and evaluations also take less time, which can greatly reduce the burden on endoscopists. In addition, artificial intelligence can also perform real-time detection and feedback on the inspection process of the endoscopist to standardize the operation of the endoscopist. AI has also shown great potential in training novice endoscopists. With the maturity of AI technology, AI has the ability to improve the detection rate of early gastric cancer in China and reduce the death rate of gastric cancer related diseases in China.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.