Evidence map›Paper›PMID 42042572›Full record

ArticleJournal of personalized medicine2026

Personalized Prediction of Postoperative Recurrence in Lung Squamous Cell Carcinoma: Integrating AI-Based Nuclear Morphometry and Clinical Data.

Tomokazu Omori, Akira Saito, Yoshihisa Shimada, Yujin Kudo, Jun Matsubayashi, Toshitaka Nagao, Masahiko Kuroda, Norihiko Ikeda

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of personalized 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

8 authors.

Tomokazu OmoriDepartment of Surgery, Tokyo Medical University, Tokyo 160-8402, Japan.
Akira SaitoDepartment of Anatomic Pathology, Tokyo Medical University, Tokyo 160-8402, Japan.
Yoshihisa ShimadaDepartment of Surgery, Tokyo Medical University, Tokyo 160-8402, Japan.ORCID 0000-0003-3811-6159
Yujin KudoDepartment of Surgery, Tokyo Medical University, Tokyo 160-8402, Japan.ORCID 0000-0003-3187-9970
Jun MatsubayashiDepartment of Anatomic Pathology, Tokyo Medical University, Tokyo 160-8402, Japan.
Toshitaka NagaoDepartment of Anatomic Pathology, Tokyo Medical University, Tokyo 160-8402, Japan.ORCID 0000-0003-2075-9738
Masahiko KurodaDepartment of AI Applied Quantitative Clinical Science, Tokyo Medical University, Tokyo 160-8402, Japan.ORCID 0000-0001-7052-4289
Norihiko IkedaDepartment of Surgery, Tokyo Medical University, Tokyo 160-8402, Japan.

Funding

Japan Society for the Promotion of Science (JSPS) 23K16581
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial intelligencelung neoplasmsprognosisrecurrencesquamous cell carcinomasupport vector machines

Identifiers

PMID42042572
PMCPMC13117173

What OpenQuestion holds

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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.