ArticleComputers in biology and medicine2018
Accurate segmenting of cervical tumors in PET imaging based on similarity between adjacent slices.
Article in Computers in biology and medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Machine and Deep Learning for the Diagnosis, Prognosis, and Treatment of Cervical Cancer: A Scoping Review.Diagnostics (Basel, Switzerland) · 2025Review
- Cervical cancer segmentation based on medical images: a literature review.Quantitative imaging in medicine and surgery · 2024Review
- A collection input based support tensor machine for lesion malignancy classification in digital breast tomosynthesis.Physics in medicine and biology · 2019Article
- Automatic PET cervical tumor segmentation by combining deep learning and anatomic prior.Physics in medicine and biology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Because in PET imaging cervical tumors are close to the bladder with high capacity for the secreted
Indexed as
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.