ArticleDiagnostics (Basel, Switzerland)2021
Development of a Machine Learning Model to Distinguish between Ulcerative Colitis and Crohn's Disease Using RNA Sequencing Data.
Article 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 18 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.
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Who cites it
18 citing papers in PubMed, 21 citations in OpenAlex.
- Aimed at Subtype Discrimination but Yielding a Shared Marker: Integrative Analysis of Blood Transcriptomes Reveals UpregulatedClinical and experimental gastroenterology · 2026Article
- Evolution of inflammatory bowel disease in Korea: a 60-year perspective on clinical and research development.Intestinal research · 2025Review
- Machine learning based gut microbiota pattern and response to fiber as a diagnostic tool for chronic inflammatory diseases.BMC microbiology · 2025Article
- Early Progression Prediction in Korean Crohn's Disease Using a Korean-Specific PrediXcan Model.International journal of molecular sciences · 2025Article
- Mendelian randomization integrated with multi-omics analysis identifies TNIK as a key gene in gut microbiota-induced IBD development.Frontiers in immunology · 2025Article
- Identifying inflammatory bowel disease subtypes: a comprehensive exploration of transcriptomic data and machine learning-based approaches.Therapeutic advances in gastroenterology · 2025Article
- Artificial intelligence use for precision medicine in inflammatory bowel disease: a systematic review.American journal of translational research · 2025Review
- Machine learning in the differential diagnosis of ulcerative colitis and Crohn's disease: a systematic review.Translational gastroenterology and hepatology · 2025Review
- Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early Detection.Diagnostics (Basel, Switzerland) · 2024Article
- The Role of Artificial Intelligence in the Diagnosis and Treatment of Ulcerative Colitis.Diagnostics (Basel, Switzerland) · 2024Review
- Review
- Profiling the inflammatory bowel diseases using genetics, serum biomarkers, and smoking information.iScience · 2023Article
- Enrichment of Activated Fibroblasts as a Potential Biomarker for a Non-Durable Response to Anti-Tumor Necrosis Factor Therapy in Patients with Crohn's Disease.International journal of molecular sciences · 2023Article
- Potential Oral Microbial Markers for Differential Diagnosis of Crohn's Disease and Ulcerative Colitis Using Machine Learning Models.Microorganisms · 2023Article
- Development of a 32-gene signature using machine learning for accurate prediction of inflammatory bowel disease.Cell regeneration (London, England) · 2023Article
- Advances in Imaging of Inflammation, Fibrosis, and Cancer in the Gastrointestinal Tract.International journal of molecular sciences · 2022Review
- Inverse and Concordant Mucosal Pathway Gene Expressions in Inflamed and Non-Inflamed Ulcerative Colitis Patients: Potential Relevance to Aetiology and Pathogenesis.International journal of molecular sciences · 2022Article
- Development of a Machine Learning Model to Predict Non-Durable Response to Anti-TNF Therapy in Crohn's Disease Using Transcriptome Imputed from Genotypes.Journal of personalized medicine · 2022Article
Corrections and comments
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Authors and funding
17 authors at 10 institutions in 1 country.
Funding
Abstract
Crohn's disease (CD) and ulcerative colitis (UC) can be difficult to differentiate. As differential diagnosis is important in establishing a long-term treatment plan for patients, we aimed to develop a machine learning model for the differential diagnosis of the two diseases using RNA sequencing (RNA-seq) data from endoscopic biopsy tissue from patients with inflammatory bowel disease (
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What OpenQuestion holds
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.