Evidence map›Paper›PMID 41307585›Full record

ArticleVirchows Archiv : an international journal of pathology2026

FigATree: a novel framework for histological subtyping and grading of lung adenocarcinoma.

Qiang Huang, Jiajun Zhang, Qiming He, Shu Wang, Qilai Zhang, Lan Lin, Xunbin Yu, Yu Wang, Yonghong He, Xin Chen and 2 more

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In one paragraph

Article in Virchows Archiv : an international journal of pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

12 authors.

Qiang Huang *Shenzhen International Graduate School, Tsinghua University, 518000, Shenzhen, P. R. China.
Jiajun Zhang *Shenzhen International Graduate School, Tsinghua University, 518000, Shenzhen, P. R. China.
Qiming He *Shenzhen International Graduate School, Tsinghua University, 518000, Shenzhen, P. R. China.
Shu WangSchool of Mechanical Engineering and Automation, Fuzhou University, 350108, Fuzhou, P. R. China.
Qilai ZhangShenzhen International Graduate School, Tsinghua University, 518000, Shenzhen, P. R. China.
Lan LinDepartment of Pathology, Fuzhou University Affiliated Provincial Hospital, 350001, Fuzhou, P. R. China.
Xunbin YuDepartment of Pathology, Fuzhou University Affiliated Provincial Hospital, 350001, Fuzhou, P. R. China.
Yu WangDepartment of Pathology, Fuzhou University Affiliated Provincial Hospital, 350001, Fuzhou, P. R. China.
Yonghong HeShenzhen International Graduate School, Tsinghua University, 518000, Shenzhen, P. R. China.
Xin ChenDepartment of Pathology, Fuzhou University Affiliated Provincial Hospital, 350001, Fuzhou, P. R. China. Docli254@126.com.
Tian GuanShenzhen International Graduate School, Tsinghua University, 518000, Shenzhen, P. R. China. guantian@sz.tsinghua.edu.cn.
Houqiang LiDepartment of Pathology, Fuzhou University Affiliated Provincial Hospital, 350001, Fuzhou, P. R. China. docli254@163.com.ORCID http://orcid.org/0000-0002-7537-7510

Funding

Joint Funds for the Innovation of Science and Technology of Fujian Province 2024Y96010076National Natural Science Foundation of China 82430062Natural Science Foundation of Fujian Province 2024J011006Shenzhen Engineering Research Centre XMHT20230115004Shenzhen Science and Technology Innovation Commission KCXFZ20201221173207022
6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) exhibits pronounced morphological heterogeneity, making accurate subtyping and grading a persistent challenge in pathology. Conventional deep learning methods often lack the granularity and interpretability required for clinical translation. We introduce FigATree, an interpretable AI framework for LUAD diagnosis that combines a foundation model-enhanced region-level encoder with an XGBoost-based pathology-informed slide-level classifier. Applied to 1186 H&E-stained whole-slide images, FigATree achieves

Indexed as

Adenocarcinoma of LungDeep LearningImage Interpretation, Computer-AssistedLung NeoplasmsHumansNeoplasm GradingDifferentiation degreeFoundation modelHistological subtypeLung adenocarcinomaXGBoost

Identifiers

PMID41307585

What OpenQuestion holds

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Registered trials

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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.