Evidence map›Paper›PMID 41374344›Full record

ArticleDiagnostics (Basel, Switzerland)2025

Multimodal-Imaging-Based Interpretable Deep Learning Framework for Distinguishing Brucella from Tuberculosis Spondylitis: A Dual-Center Study.

Mayidili Nijiati, Mei Zhang, Chencui Huang, Xinyue Chou, Lingyan Shen, Haiting Ma, Zhenwei Ren, Maimaitishawutiaji Maimaiti, Yi You, Xiaoguang Zou and 1 more

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Mayidili NijiatiDepartment of Radiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830002, China.
Mei ZhangDepartment of Radiology, Xinjiang Medical University Affiliated Fourth Hospital, Urumqi 830002, China.
Chencui HuangDepartment of Deepwise AI Lab, Hangzhou Deepwise & League of PHD Technology Co., Ltd., Hangzhou 830054, China.
Xinyue ChouDepartment of Radiology, Xinjiang Medical University Affiliated Fourth Hospital, Urumqi 830002, China.
Lingyan ShenDepartment of Deepwise AI Lab, Hangzhou Deepwise & League of PHD Technology Co., Ltd., Hangzhou 830054, China.
Haiting MaDepartment of Radiology, Xinjiang Medical University Affiliated Fourth Hospital, Urumqi 830002, China.
Zhenwei RenDepartment of Radiology, Xinjiang Medical University Affiliated Fourth Hospital, Urumqi 830002, China.
Maimaitishawutiaji MaimaitiDepartment of Spinal Surgery, The First People's Hospital of Kashi Prefecture, Kashi 844000, China.
Yi YouDepartment of Deepwise AI Lab, Hangzhou Deepwise & League of PHD Technology Co., Ltd., Hangzhou 830054, China.
Xiaoguang ZouXinjiang Key Laboratory of Artificial Intelligence Assisted Imaging Diagnosis, Kashi 844000, China.
Yunling WangDepartment of Radiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830002, China.

Funding

National Key R&D Program of China National Key R&D Program of China [Grant number 2022ZD0160705Science & Technology Program of Kashi Prefecture KS2022007
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

brucella spondylitisdeep learningmultimodal imagingtuberculosis spondylitis

Identifiers

PMID41374344
PMCPMC12691320

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.