Evidence map›Paper›PMID 42484898›Full record

ArticleEuropean radiology2026

Letter to the Editor: Deep learning network for predicting meningioma grade and Ki-67 expression: tumor location stratification.

Xingyun Yang, Qichen Pan, Cunyi Zou

Abstract readLetterComment
PubMed Publisher
In one paragraph

Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Xingyun Yang *Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, China.
Qichen Pan *Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, China.
Cunyi ZouDepartment of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, China. cnzoucunyi@126.com.ORCID http://orcid.org/0009-0008-0237-1020

Funding

the Natural Science Foundation of Liaoning Province 2020-BS-105, 2023-MSLH-401
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.