Research topics
AI and data science articles covering predictive models, machine learning, algorithms, and data-driven IBD research.
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Dysplasia detection during colonoscopy is central to preventing colorectal cancer in people with IBD. AI tools could help, but current models often fail in inflamed or IBD-specific settings, so this review outlines...
Automated, quantitative analysis of pathology slides could reduce variability in histological scoring and help track histological healing — a growing therapeutic target in ulcerative colitis.
These methods could help researchers and clinicians better identify which treatments are likely to work for which patients by combining trials and EHR data, accounting for multiple outcomes and missing data — relevant to...
Non-invasive, portable tests that can track inflammation more frequently could help patients and clinicians monitor disease activity between clinic visits and guide treatment decisions without repeated invasive...
The work highlights macrophage metabolic programs and specific genes that may help classify UC molecular subtypes and suggest candidate biomarkers or therapeutic targets related to macrophage-driven inflammation.
Faster, reliable reading of capsule endoscopy videos could shorten diagnostic delays and make small-bowel evaluation easier for people with suspected Crohn’s disease. If AI preserves accuracy while reducing review time,...
Based on the title and source metadata, this appears to be a basic science related to Ulcerative colitis, Inflammatory bowel disease, and AI and data science. The original article is from International journal of surgery...
The study suggests that air pollutant NO2 may promote a perforin-producing CD8+ T cell response linked to colonic inflammation in UC and highlights CDC25B as a potential mechanistic link—information that could guide...
The study provides a more rigorous, leakage-free machine-learning analysis of a major IBD microbiome cohort and proposes reproducible microbial and metabolic pathway candidates that could eventually help IBD diagnosis or...
Identifying common multimorbidity patterns and using machine learning to predict premature mortality could help health systems and clinicians prioritize integrated care for people with IBD, potentially improving outcomes...
AI tools are being tailored to IBD care; this study suggests supervised fine-tuned LLMs may help with patient communication and workflow but currently lack reliable diagnostic accuracy. Patients and clinicians should...
Registries that automatically extract clinical data with AI/NLP can speed research, help identify patient cohorts for studies or trials, and may eventually support better clinical decision-making for people with IBD....
Researchers are exploring ways to prioritize who needs colonoscopy sooner; adding TCM features to prediction models might change triage performance. Patients and clinicians interested in pre-endoscopic risk tools or...
The work aims to predict relapse and personalize herbal maintenance dosing for UC, which matters because better risk stratification and tailored management could reduce relapses and avoid unnecessary treatment changes.
The project aims to enable simultaneous RNA-level profiling of microbes and host cells from human biopsies, which could reveal early microbial and host gene-expression patterns linked to subclinical Crohn’s disease and...
AI chatbots are increasingly used for health information. If chatbot answers about IBD nutrition are inaccurate or hard to read, patients could be confused or misinformed. This study assesses those risks for ChatGPT-3.5.
The study proposes new biomarker candidates (C5AR1, KDM2A, HCAR3) and microbiota-derived metabolites that might interact with those targets. If validated, that could guide future diagnostic tests or microbiome-targeted...
Improving accuracy of IBD case identification in EMRs can make research and registries more reliable, reduce misclassification, and help ensure studies and quality programs use the right patient groups.
The study introduces a phylogeny-aware AI method that may improve detection and interpretation of microbiome signatures linked to IBD and colorectal cancer, which could help research into microbial biomarkers relevant to...
The study uses generative AI and microbiome/RNA data to search for biomarkers of intestinal fibrosis in Crohn’s disease, which could help spot scarring earlier and potentially prevent worsening complications like...
This project aims to improve prediction of autoimmune disease onset and immunotherapy-related autoimmunity by combining genetics and plasma proteins.
Researchers are using a new MRI-based index (ANDI) to look for early brain changes linked to Parkinson’s disease and dementia in groups at higher risk, including people with inflammatory bowel disease. If successful, the...
Identifies gene and microbiome patterns linked to progression from inflammation to irreversible bowel fibrosis in Crohn’s disease, which could eventually help predict who is at higher risk and inform prevention...
This study suggests that specific gut bacteria targeted by systemic IgG are associated with UC activity and inflammation, which could eventually help identify microbial signals linked to flares or systemic inflammation.
Fibrosis (irreversible bowel scarring) is a major cause of surgery in Crohn’s disease. This study points to molecular and microbiome patterns that may help predict or distinguish fibrosis from active inflammation, which...
Fibrosis (irreversible bowel scarring) is a major cause of surgery in Crohn’s disease. Identifying molecular and microbial markers tied to fibrosis could eventually help predict who’s at higher risk and guide earlier,...
The work points to measurable molecular and microbial patterns that may help distinguish treatable inflammation from progressive fibrosis and suggests AI could aid in building predictive tools from limited samples —...
AI tools could make objective disease assessment faster and more consistent, help detect inflammation beyond what symptoms suggest, and ultimately support more personalized treatment choices for people with Crohn’s...
The study links shared gene-expression patterns between IBD and ankylosing spondylitis and highlights STAT3 as a potential shared biomarker or therapeutic target, which could be relevant for understanding overlapping...
AI could help make IBD assessments (endoscopy, histology, imaging, biomarkers) more objective and faster, which may improve monitoring, treatment selection, and early detection of complications for people with Crohn’s...
AI models that combine CTE/MRE imaging with clinical and molecular data could improve objective classification of small-bowel Crohn's disease and help predict which patients are likely to respond to medical therapy...
People with UC often seek dietary strategies to help manage inflammation; this study uses AI and docking to prioritize polyphenols and foods for future testing, which could guide research and eventually inform dietary...
People with Crohn's disease or ulcerative colitis might see more AI-based prognostic tools in the literature, but this review shows most models are not yet proven ready for clinical use because they lack key validation...
Handheld IUS could make noninvasive bowel assessment faster and more accessible for people with IBD, helping with triage and short-term monitoring without immediately resorting to endoscopy or advanced imaging.
IOIBD’s consensus frameworks and educational programs shape how IBD is studied and treated worldwide — affecting trial design, treatment goals, patient-reported outcome measures, and clinical guidance that patients and...
AI could help standardize endoscopic and histologic scoring in IBD, speed capsule endoscopy interpretation, and improve lesion detection — changes that might affect monitoring and diagnosis workflows for people with...
An AI-derived score that combines inflammation severity and extent may better predict relapse risk in ulcerative colitis than severity alone. That could help identify patients in endoscopic remission who still face...
The work suggests soluble factors present in fecal filtrates from active UC patients can provoke proinflammatory responses in a controlled intestine-on-chip model, supporting the idea that microbiome-derived metabolites...
Automated, consistent scoring of the UCEIS could reduce subjectivity and variability in endoscopic assessment of ulcerative colitis, which matters for clinical trials, central reading, and potentially treatment decisions...
ECCO 2026 presented multiple studies that could change IBD care across prevention, medical therapy (including pediatric data), complication‑directed strategies (perianal fistula), and technology‑assisted monitoring....
Kidney dysfunction can occur in people with IBD and may be under-recognized. A validated prediction model could help clinicians identify IBD patients at higher risk and prompt earlier monitoring or interventions.
A validated pre-endoscopic model could help estimate UC disease extent before colonoscopy, aiding clinical triage and planning without replacing endoscopy.
This research links molecular subtypes of ulcerative colitis to infliximab (anti-TNF) response using an interpretable machine-learning method, which could help identify which patients are more or less likely to respond...
AI could help identify dietary patterns, predict which patients might benefit from specific nutrition approaches, and provide personalized nutrition support — potentially improving inflammation and gut microbiome...
AI could help make assessments (endoscopy, histology, imaging) more objective and combine complex data to better predict disease course—potentially improving personalized care planning for people with IBD.
This study suggests that subgrouping autoimmune diseases by a Traditional Chinese Medicine phenotype (Dampness ZHENG) corresponds to distinct T‑ and B‑cell receptor patterns.
A more detailed, reproducible measure of endoscopic inflammation could better reflect total disease burden and reduce variability from human readers. That may matter for monitoring disease activity, judging treatment...
A coordinated national research network can accelerate studies that matter to people with IBD—like tracking real-world disease patterns, testing diet and psychosocial approaches, improving monitoring with biomarkers and...
