Evidence map›Paper›PMID 40805131›Full record

ArticleCancers2025

Histological Image Classification Between Follicular Lymphoma and Reactive Lymphoid Tissue Using Deep Learning and Explainable Artificial Intelligence (XAI).

Joaquim Carreras, Haruka Ikoma, Yara Yukie Kikuti, Shunsuke Nagase, Atsushi Ito, Makoto Orita, Sakura Tomita, Yuki Tanigaki, Naoya Nakamura, Yohei Masugi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
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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.

Joaquim CarrerasDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.ORCID 0000-0002-6129-8299
Haruka IkomaDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.
Yara Yukie KikutiDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.
Shunsuke NagaseDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.ORCID 0000-0002-6130-3879
Atsushi ItoDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.
Makoto OritaDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.
Sakura TomitaDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.
Yuki TanigakiDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.ORCID 0009-0005-0542-2549
Naoya NakamuraDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.
Yohei MasugiDepartment of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan.

Funding

Ministry of Education, Culture, Sports, Science and Technology 23K06454
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial intelligenceconvolutional neural networkdeep learningexplainable artificial intelligencefollicular hyperplasiafollicular lymphomareactive lymphoid tissue

Identifiers

PMID40805131
PMCPMC12345699

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.