ReviewFrontiers in bioengineering and biotechnology2021
Artificial Intelligence Enhances Studies on Inflammatory Bowel Disease.
Review in Frontiers in bioengineering and biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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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.
The trial behind it
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
17 citing papers in PubMed, 25 citations in OpenAlex.
- MicroRNA‑microbiome cross‑kingdom networks drive inflammatory bowel disease through dynamic regulatory ecosystems (Review).International journal of molecular medicine · 2026Review
- Explainable artificial intelligence for personalized management of inflammatory bowel disease: A minireview of recent advances.World journal of gastroenterology · 2025Review
- Genetic factors that predict response and failure of biologic therapy in inflammatory bowel disease.World journal of experimental medicine · 2025Review
- Multi-omics perspective: mechanisms of gastrointestinal injury repair.Burns & trauma · 2025Review
- Novel bioparameters derived from bioimpedance measurements for accurate prediction of weight status in infant-juvenile individuals: A regression analysis.Journal of electrical bioimpedance · 2025Article
- Machine learning in the differential diagnosis of ulcerative colitis and Crohn's disease: a systematic review.Translational gastroenterology and hepatology · 2025Review
- Use of Modified YOLOv5 Algorithm in the Differential Diagnosis of Colonic Crohn's Disease and Ulcerative Colitis on CTE Images.Gastroenterology research and practice · 2025Article
- Precision Medicine in Inflammatory Bowel Disease: A Spotlight on Emerging Molecular Biomarkers.Biomedicines · 2024Review
- The Role of Artificial Intelligence in the Diagnosis and Treatment of Ulcerative Colitis.Diagnostics (Basel, Switzerland) · 2024Review
- Endoscopy-based IBD identification by a quantized deep learning pipeline.BioData mining · 2023Article
- Artificial Intelligence in Inflammatory Bowel Disease Endoscopy: Implications for Clinical Trials.Journal of Crohn's & colitis · 2023Review
- The Role of Artificial Intelligence in Monitoring Inflammatory Bowel Disease-The Future Is Now.Diagnostics (Basel, Switzerland) · 2023Review
- Machine learning models and over-fitting considerations.World journal of gastroenterology · 2022Article
- Classification of the Confocal Microscopy Images of Colorectal Tumor and Inflammatory Colitis Mucosa Tissue Using Deep Learning.Diagnostics (Basel, Switzerland) · 2022Article
- Predictive models for endoscopic disease activity in patients with ulcerative colitis: Practical machine learning-based modeling and interpretation.Frontiers in medicine · 2022Article
- Application of Metal-Based Nanozymes in Inflammatory Disease: A Review.Frontiers in bioengineering and biotechnology · 2022Review
- The global research of artificial intelligence on inflammatory bowel disease: A bibliometric analysis.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inflammatory bowel disease (IBD), which includes ulcerative colitis (UC) and Crohn's disease (CD), is an idiopathic condition related to a dysregulated immune response to commensal intestinal microflora in a genetically susceptible host. As a global disease, the morbidity of IBD reached a rate of 84.3 per 100,000 persons and reflected a continued gradual upward trajectory. The medical cost of IBD is also notably extremely high. For example, in Europe, it has €3,500 in CD and €2,000 in UC per patient per year, respectively. In addition, taking into account the work productivity loss and the reduced quality of life, the indirect costs are incalculable. In modern times, the diagnosis of IBD is still a subjective judgment based on laboratory tests and medical images. Its early diagnosis and intervention is therefore a challenging goal and also the key to control its progression. Artificial intelligence (AI)-assisted diagnosis and prognosis prediction has proven effective in many fields including gastroenterology. In this study, support vector machines were utilized to distinguish the significant features in IBD. As a result, the reliability of IBD diagnosis due to its impressive performance in classifying and addressing region problems was improved. Convolutional neural networks are advanced image processing algorithms that are currently in existence. Digestive endoscopic images can therefore be better understood by automatically detecting and classifying lesions. This study aims to summarize AI application in the area of IBD, objectively evaluate the performance of these methods, and ultimately understand the algorithm-dataset combination in the studies.
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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.