Evidence map›Paper›PMID 40426621›Full record

ArticleBrain sciences2025

Bayesian-Optimized Convolutional Neural Networks for Classifying Primary Tumor Origin of Brain Metastases from MRI.

Jawed Nawabi, Semil Eminovic, Alexander Hartenstein, Georg Lukas Baumgaertner, Nils Schnurbusch, Madhuri Rudolph, David Wasilewski, Julia Onken, Eberhard Siebert, Edzard Wiener and 6 more

Abstract read
In one paragraph

Article in Brain sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Jawed NawabiDepartment of Neuroradiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.ORCID 0000-0002-1137-0643
Semil EminovicDepartment of Radiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.ORCID 0009-0001-1871-2976
Alexander HartensteinMedical Affairs and Pharmacovigilance, Bayer AG, 13353 Berlin, Germany.
Georg Lukas BaumgaertnerDepartment of Radiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.ORCID 0000-0003-3046-0019
Nils SchnurbuschDepartment of Radiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.
Madhuri RudolphDepartment of Radiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.
David WasilewskiDepartment of Neurosurgery, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Dusseldorf, 40225 Dusseldorf, Germany.
Julia OnkenDepartment of Neurosurgery, Charité-Universitätsmedizin, 10117 Berlin, Germany.
Eberhard SiebertDepartment of Neuroradiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.ORCID 0000-0001-7395-6546
Edzard WienerDepartment of Neuroradiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.
Georg BohnerDepartment of Neuroradiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.ORCID 0000-0002-1919-092X
Andrea Dell'OrcoDepartment of Neuroradiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.ORCID 0000-0002-3964-8360
Mike P WattjesDepartment of Neuroradiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.
Bernd HammDepartment of Radiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.
Uli FehrenbachDepartment of Radiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.ORCID 0000-0003-3622-3268
Tobias PenzkoferDepartment of Radiology, Charité-Universitätsmedizin, 10117 Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Bayesian optimizationbrain metastasesneural networks

Identifiers

PMID40426621
PMCPMC12110443

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.