ReviewSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2021
[Application and Progress of Convolutional Neural Network-based Pathological Diagnosis of Gastric Cancer].
Review in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Convolutional neural network-based artificial intelligence for the diagnosis of early esophageal cancer based on endoscopic images: A meta-analysis.Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology AssociationPooled it
- A multiomics Mendelian randomization study on PANoptosis-related genes and gastric cancer risk.The Journal of international medical research · 2026Article
- Application of deep learning convolutional neural networks to identify gastric squamous cell carcinoma in mice.Frontiers in medicine · 2025Article
- Comprehensive analysis of disulfidptosis related genes and prognosis of gastric cancer.World journal of clinical oncology · 2023Article
- The Feasibility of Applying Artificial Intelligence to Gastrointestinal Endoscopy to Improve the Detection Rate of Early Gastric Cancer Screening.Frontiers in medicine · 2022Review
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Authors and funding
5 authors.
Funding
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Abstract
The incidence of gastric cancer is the highest among all kinds of malignant tumors in China. Because gastric cancer is very hard to identify in its early stage, the early diagnosis rate of gastric cancer in China is relatively low. At present, the pathological diagnosis of gastric cancer mainly depends on the diagnosis of pathologists. However, the gradual improvement of people's living standards and the growing demand for medical and health care have exacerbated the shortage of medical resources, which has become a even more serious problem. Therefore, there is an urgent need for new technologies to help deal with this challenge. In recent years, with the rapid development of artificial intelligence (AI) and digital pathology, AI-aided pathological diagnosis based on convolutional neural network (CNN) as the core technology is showing promises for improving the diagnostic efficiency of gastric cancer. It is also of great significance for the early diagnosis and treatment of the disease and the reduction of its high incidence and mortality. We herein summarize the application and progress of deep-learning CNN in pathological diagnosis of gastric cancer, as well as the existing problems and prospects of future development.
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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.