ArticleFrontiers in medicine2021
Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.
Article in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Radiomics of pituitary adenoma using computer vision: a review.Medical & biological engineering & computing · 2024Pooled it
- Application of artificial intelligence and radiomics in pituitary neuroendocrine and sellar tumors: a quantitative and qualitative synthesis.Neuroradiology · 2022Pooled it
- A stacking model for AI-assisted diagnosis of suspected pituitary microadenomas on non-contrast T1COR MRI: a multicenter reader study on bridging the experience gap.Neuroradiology · 2026Article
- Article
- The current state of MRI-based radiomics in pituitary adenoma: promising but challenging.Frontiers in endocrinology · 2024Review
- Applications and Integration of Radiomics for Skull Base Oncology.Advances in experimental medicine and biology · 2024Review
- CT-based identification of pediatric non-Wilms tumors using convolutional neural networks at a single center.Pediatric research · 2023Article
- Clinical application of artificial intelligence algorithms in detecting clival remodeling in the setting of pituitary neuroendocrine tumors/pituitary adenomas.Frontiers in neurologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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.