Research topics
AI and data science articles covering predictive models, machine learning, algorithms, and data-driven IBD research.
Page 1 of 3 · 114 articles
People with Crohn’s disease who have had, or will have, intestinal surgery may benefit from better tools to predict early complications and endoscopic recurrence. Predictive models could help tailor follow-up and...
Multi-omics and AI approaches could improve biomarker discovery and predictive models that matter for earlier diagnosis and personalised treatment strategies in IBD, but practical use is limited today by data and...
People with Crohn's disease may be interested because the paper provides molecular hypotheses linking acupuncture to immune-related pathways (neutrophils, M2 macrophages) and nominates FER as a potential...
If validated, antibody-based signatures could enable much earlier detection of IBD and help identify people at risk of more severe Crohn’s disease years before symptoms—potentially opening opportunities for research on...
This study aims to measure how much time people with ulcerative colitis spend with objectively uncontrolled inflammation and to compare real-world outcomes of different initial advanced-therapy choices and...
Cardiovascular disease is an important extraintestinal concern for people with IBD, and current risk scores may miss IBD-specific drivers. This study aims to track heart and vascular events in IBD and find biomarkers...
People with Crohn’s disease or ulcerative colitis may have higher cardiovascular risk; this prospective study aims to measure how often major heart and vascular events occur in IBD and to find biological and clinical...
Predicting early need for infliximab could help identify children with Crohn’s disease who may benefit from earlier biologic therapy instead of prolonged conventional treatment. A reliable prediction tool may shorten...
Protein biomarkers that predict IBD years before diagnosis could enable earlier detection, inform risk-stratified monitoring, and reveal early disease pathways that might be targeted to prevent or delay onset.
Fusing blood tests, CT enterography radiomics, and deep-learning analysis of deep small-bowel endoscopy images may improve detection of active small-bowel Crohn’s disease — a common clinical challenge because many...
Noninvasive imaging that better separates inflammation from fibrosis and detects penetrating complications could change monitoring and treatment decisions in IBD and reduce radiation exposure for patients needing...
Earlier identification of people likely to develop IBD could shorten diagnostic delays that are linked to worse outcomes, and an automated EHR model might help target who should get earlier evaluation.
A breath-based VOC test could offer a noninvasive, point-of-care way to help detect or screen for colon diseases including IBD. This study shows preliminary promise—especially for ulcerative colitis—but is early-stage...
The study points to a possible noninvasive brain-based biomarker that correlates with intestinal fibrosis severity in Crohn’s disease, a complication that’s hard to detect and treat. This could eventually help identify...
Standardized, automated severity stratification at diagnosis could help guide early treatment planning and comparability across centers. An AI approach that approximates expert consensus may reduce variability in initial...
This paper maps where and how mitochondria-related IBD research has grown and what themes (like mitophagy, metabolism, and machine learning) are emerging — useful for researchers, funders, and clinicians tracking...
Faster, more sensitive capsule endoscopy reading could catch more Crohn’s-related ulcers that might otherwise be missed and reduce the time clinicians spend reviewing long video exams. However, AI increased false...
Accurate, consistent severity grading at diagnosis shapes initial treatment decisions in Crohn’s disease. AI that can reproduce expert severity assessments from small labeled datasets could help standardize grading and...
If validated, early bedside ultrasound changes could let clinicians identify within days whether steroids or biologics are working, enabling faster treatment adjustments and potentially avoiding prolonged ineffective...
Predicting who will relapse after stopping anti-TNF drugs could help avoid unnecessary flares or unnecessary ongoing treatment. A biopsy-based transcriptomic test could be a useful decision tool if validated.
This study links a neutrophil protein (ANXA3) to both ulcerative colitis and ischaemic stroke and suggests a compound (ginsenoside Rb1) can bind ANXA3 and reduce neutrophil hyperactivation in lab tests — a potential...
Microbiome patterns in this study were linked to inflammation (fecal calprotectin) and higher chance of needing treatment escalation. If validated, enterotype stratification could help predict disease course or tailor...
The study proposes a machine learning approach to identify SNPs linked to Crohn’s disease risk, which could help researchers prioritize genetic variants for further study and, eventually, contribute to risk prediction or...
If genetics helps explain who develops Crohn’s disease, better ways to pick the handful of important variants could speed discovery of biological mechanisms and future tests.
AI models are being developed to support IBD care (activity scoring, risk prediction), but most studies are retrospective and don’t yet demonstrate that AI outputs reliably change clinical decisions or improve outcomes....
If validated, AI-enhanced vascular assessment during endoscopy could give clearer, more reproducible information about mucosal and histologic healing — which matters for monitoring disease activity and guiding treatment...
Non-specialist physicians often manage IBD where specialists are scarce. If reliable, AI tools could improve non-specialists' clinical reasoning and decision-making for IBD care.
A company claims a novel quantum-based method has highlighted potential drug targets in diseases including Crohn’s disease, which could influence future drug discovery approaches. Investment by CDT Equity signals...
Understanding how individual diet and microbiome patterns relate to disease activity could help create personalized dietary approaches for children with Crohn's disease and improve monitoring using home fecal...
AI-assisted detection tools and disease-specific optical classifications could improve lesion detection and real-time characterization during UC surveillance, potentially affecting surveillance accuracy and...
If validated, prealbumin — a routine blood protein test reflecting nutrition and inflammation — could help predict who with Crohn’s disease is more likely to need abdominal surgery or to have endoscopic recurrence after...
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 Toxicological Research.
Based on the title and source metadata, this appears to be a basic science related to Ulcerative colitis, AI and data science, and Research and clinical trials. The original article is from BMC Medical Research...
Identifies a fibroblast senescence signature and highlights ADAMTS2 as a candidate biomarker linked to inflammation and fibrosis in IBD, which could guide future diagnostic or therapeutic research relevant to Crohn’s...
AI tools for endoscopic and multimodal IBD assessment could make scoring and monitoring more objective and consistent, which matters for treatment decisions and tracking remission or relapse. The review also flags...
Distinguishing Crohn’s disease from intestinal tuberculosis is a frequent problem in TB-endemic areas; a validated mobile ML tool could help clinicians make more accurate, faster diagnostic decisions and avoid...
Predicting which children with Crohn disease will need surgery — and roughly when — could help families and clinicians plan treatments, monitoring, and discussions about elective bowel resection earlier in the disease...
This work looks for molecular signals that might help explain how long-term ulcerative colitis can be connected to higher colorectal cancer risk. Identifying shared genes and spatial patterns could eventually guide...
Automated analysis of full-length endoscopy videos could standardise assessment of UC activity, identify spatial patterns of inflammation, and better estimate histological healing—information that may influence treatment...
A model that predicts one-year risks for surgery and complications by Montreal phenotype could help identify patients at higher short-term risk and guide research into targeted monitoring or interventions.
The study tests a molecular technique (ATR-FTIR) with machine learning on biopsy tissue to find signals linked to future dysplasia/CRC risk in IBD — a potential complement to colonoscopic surveillance if validated.
The work identifies factors that predict loss of response to infliximab and suggests maintenance drug levels are the strongest predictor, which could influence monitoring strategies for people with Crohn's disease on...
Intestinal ultrasound can assess IBD inflammation without radiation but interpretation varies by operator. Developing AI tools to measure bowel wall thickness and other features could standardize and speed image...
The intestinal barrier changes in inflammation and can alter how oral nanocarriers interact with mucus and epithelium; understanding this is important for designing delivery systems that achieve local therapeutic benefit...
Researchers and clinicians interested in cross-disease host–microbe interactions may find that an IBD–CRC shared microbial/host signature could have prognostic importance beyond the gut, here in bladder cancer.
Fatigue affects more than half of people with IBD and is a leading cause of impaired quality of life. A machine-learning approach that identifies distinct patient-level patterns may help researchers and clinicians...
AMPs are central to gut immune balance and are being explored as new therapies for IBD and related gut diseases. For people with Crohn’s or IBD, understanding AMPs helps explain research directions aimed at restoring...
Identifies a stromal-cell subset marked by TIMP1 that may play a role in UC pathogenesis and might serve as a candidate biomarker or therapeutic target; useful for researchers and clinicians following emerging...
