ArticleComputational and mathematical methods in medicine2022
Deep Learning-Based Ultrasound Combined with Gastroscope for the Diagnosis and Nursing of Upper Gastrointestinal Submucous Lesions.
Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 3 citations in OpenAlex.
- Outcome of Nursing Based on Health Belief United with Knowledge, Belief, and Practice Mode on Gastroscopy of Patients with Gastric Cancer.Computational and mathematical methods in medicine · 2022Trial
- Temporal Dynamic Machine Learning Prediction of Postoperative Gastrointestinal Dysfunction Duration in Esophageal Cancer: Integrating Preoperative and Perioperative Routine Blood Temporal Data and Dynamic Ultrasonic Features.International journal of general medicine · 2026Article
- Humanistic and graded psychological nursing care for patients undergoing endoscopic submucosal dissection of gastrointestinal tumors.World journal of gastrointestinal surgery · 2025Article
- Hypoxemia prediction model based on XGBoost during sedation for gastrointestinal endoscopy.Frontiers in medicine · 2025Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study focused on the diagnostic value of deep learning-based ultrasound combined with gastroscope examination for upper gastrointestinal submucous lesions and nursing. A total of 104 patients with upper gastrointestinal submucous lesions diagnosed in hospital were selected as the research subjects. In this study, the feed forward denoising convulsive neural network (DnCNN) was improved, and the n-DnCNN model was designed and applied to ultrasonic image processing. The peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of Gaussian filtering, NL-means, and DnCNN were then compared with n-DnCNN. Subsequently, the distribution and types of submucosal lesions in different parts of the upper digestive tract were analyzed by ultrasound combined with gastroscope and gastroscope examination alone, and the diagnostic performance of this method was evaluated. The results showed that the average PSNR and SSIM of the n-DnCNN model were 33.01 dB and 0.87, respectively, which were significantly higher than GF, NL-means, and DnCNN algorithms, and the difference was statistically significant (
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