Evidence map›Paper›PMID 42513318›Full record

ArticleJournal of clinical medicine2026

Convolutional Neural Network-Based Age Prediction from Cephalometric Images and Analysis of Site-Specific Associations.

Toshiro Emori, Ryo Hamanaka, Runa Yamaguchi-Higuchi, Yui Horiguchi-Nakayama, Sayaka Iwata, Kazuhiro Ogawa, Arina Kitaura, Hiroya Komaki, Jun-Ya Tominaga, Noriaki Yoshida

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical medicine, 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

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

10 authors.

Toshiro EmoriDepartment of Orthodontics, Nagasaki University Hospital, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.
Ryo HamanakaDepartment of Orthodontics and Dentofacial Orthopedics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.ORCID 0000-0002-6345-1621
Runa Yamaguchi-HiguchiDepartment of Orthodontics, Nagasaki University Hospital, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.
Yui Horiguchi-NakayamaDepartment of Orthodontics and Dentofacial Orthopedics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.
Sayaka IwataDepartment of Orthodontics and Dentofacial Orthopedics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.
Kazuhiro OgawaDepartment of Orthodontics and Dentofacial Orthopedics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.
Arina KitauraDepartment of Orthodontics and Dentofacial Orthopedics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.
Hiroya KomakiDepartment of Orthodontics, Nagasaki University Hospital, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.ORCID 0000-0002-3008-9523
Jun-Ya TominagaDepartment of Orthodontics and Dentofacial Orthopedics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.
Noriaki YoshidaDepartment of Orthodontics and Dentofacial Orthopedics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan.

Funding

Japan Society for the Promotion of Science 24K13175
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

ConvNeXt-Tconvolutional neural networkcraniofacial growth predictionlateral cephalometric radiographsResNet50

Identifiers

PMID42513318
PMCPMC13412293

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.