ReviewAbdominal imaging2012
A computer-assisted model for detection of MRI signs of Crohn's disease activity: future or fiction?
Review in Abdominal imaging, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 14 citations in OpenAlex.
- A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology.Diagnostics (Basel, Switzerland) · 2021Review
- Emerging use of artificial intelligence in inflammatory bowel disease.World journal of gastroenterology · 2020Review
- Review
- The role of artificial intelligence in colon polyps detection.Gastroenterology and hepatology from bed to bench · 2020Review
- Semiautomatic Assessment of the Terminal Ileum and Colon in Patients with Crohn Disease Using MRI (the VIGOR++ Project).Academic radiology · 2018Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Magnetic resonance imaging is increasingly used for abdominal evaluation and is more and more considered as the optimal imaging technique for detection of mural inflammation in patients with Crohn's disease. Grading the disease activity is important in daily clinical practice to monitor the medical treatment and is assessed by evaluating different magnetic resonance imaging features. Unfortunately, only moderate interobserver agreement is reported for most of the subjective features and should be improved. A computer-assisted model for automatic detection of abnormalities, ability to grade disease severity, and thereby influence clinical disease management based on magnetic resonance imaging is missing. Recent techniques have focused on semi-automated methods for classification and segmentation of the bowel and also on objective measurement of bowel wall enhancement using absolute T1-values or dynamic contrast-enhanced imaging. This article reviews the available computerized techniques, as well as preferred developments.
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Identifiers
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.