ReviewDiagnostics (Basel, Switzerland)2021
Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
15 citing papers in PubMed.
- Exploring the potential of artificial intelligence in assessing the risk of gastric neoplastic lesions in patients with corpus atrophic gastritis.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Article
- Automated assessment of small bowel and colon cleansing in enteroscopy using a convolutional neural network.Endoscopy international open · 2026Article
- Artificial Intelligence in Thoracic Surgery: Transforming Diagnostics, Treatment, and Patient Outcomes.Diagnostics (Basel, Switzerland) · 2025Review
- A recurrent multimodal sparse transformer framework for gastrointestinal disease classification.Scientific reports · 2025Article
- The Human Voice as a Digital Health Solution Leveraging Artificial Intelligence.Sensors (Basel, Switzerland) · 2025Review
- Large Language Models in Gastroenterology and Gastrointestinal Surgery: A New Frontier in Patient Communication and Education.Gastroenterology research · 2025Review
- Software as a Medical Device (SaMD) in Digestive Healthcare: Regulatory Challenges and Ethical Implications.Diagnostics (Basel, Switzerland) · 2024Review
- Convolutional Neural Network Model for Intestinal Metaplasia Recognition in Gastric Corpus Using Endoscopic Image Patches.Diagnostics (Basel, Switzerland) · 2024Article
- Design of a Convolutional Neural Network as a Deep Learning Tool for the Automatic Classification of Small-Bowel Cleansing in Capsule Endoscopy.Medicina (Kaunas, Lithuania) · 2023Article
- The Promise of Artificial Intelligence in Digestive Healthcare and the Bioethics Challenges It Presents.Medicina (Kaunas, Lithuania) · 2023Review
- Application of Artificial Intelligence in Measuring Novel pH-Impedance Metrics for Optimal Diagnosis of GERD.Diagnostics (Basel, Switzerland) · 2023Review
- Article
- Artificial Intelligence for Upper Gastrointestinal Endoscopy: A Roadmap from Technology Development to Clinical Practice.Diagnostics (Basel, Switzerland) · 2022Review
- Pernicious Anemia: The Hematological Presentation of a Multifaceted Disorder Caused by Cobalamin Deficiency.Nutrients · 2022Review
- Efficient Synchronous Real-Time CADe for Multicategory Lesions in Gastroscopy by Using Multiclass Detection Model.BioMed research international · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of convolutional neural networks has achieved impressive advances of machine learning in recent years, leading to an increasing use of artificial intelligence (AI) in the field of gastrointestinal (GI) diseases. AI networks have been trained to differentiate benign from malignant lesions, analyze endoscopic and radiological GI images, and assess histological diagnoses, obtaining excellent results and high overall diagnostic accuracy. Nevertheless, there data are lacking on side effects of AI in the gastroenterology field, and high-quality studies comparing the performance of AI networks to health care professionals are still limited. Thus, large, controlled trials in real-time clinical settings are warranted to assess the role of AI in daily clinical practice. This narrative review gives an overview of some of the most relevant potential applications of AI for gastrointestinal diseases, highlighting advantages and main limitations and providing considerations for 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.