Evidence map›Paper›PMID 40568191›Full record

ArticleFrontiers in medicine2025

Artificial intelligence-based model for diagnosing

Kehan Teng, Lihua Ren, Xiaoyu Yan, Yawei Duan, Zhe Chen, Hansheng Li, Lihua Zhang, Lei Cui

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in medicine, 2025. 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.

Kehan Teng *Department of Pathology, Zhongda Hospital, Southeast University School of Medicine, Nanjing, Jiangsu, China.
Lihua Ren *Department of Gastroenterology, Zhongda Hospital, Southeast University School of Medicine, Nanjing, Jiangsu, China.
Xiaoyu Yan *School of Information Science and Technology, Northwest University, Xi'an, China.
Yawei DuanDepartment of Pathology, Zhongda Hospital, Southeast University School of Medicine, Nanjing, Jiangsu, China.
Zhe ChenDepartment of Pathology, Zhongda Hospital, Southeast University School of Medicine, Nanjing, Jiangsu, China.
Hansheng LiSchool of Information Science and Technology, Northwest University, Xi'an, China.
Lihua ZhangDepartment of Pathology, Zhongda Hospital, Southeast University School of Medicine, Nanjing, Jiangsu, China.
Lei CuiSchool of Information Science and Technology, Northwest University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Methods: Here, we developed three multi-instance learning (MIL) models: AB-MIL, DS-MIL, and Trans-MIL, to automatically detect Results: All three models demonstrated good diagnostic performance in predicting Discussion: Our research presents an AI - based predictive model for

Indexed as

artificial intelligencechronic gastritisgastric mucosal biopsyHelicobacter pyloripathological diagnosis

Identifiers

PMID40568191
PMCPMC12187772

What OpenQuestion holds

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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.