Evidence map›Paper›PMID 36148014›Full record

ArticleFrontiers in molecular biosciences2022

Multimodal ultrasound fusion network for differentiating between benign and malignant solid renal tumors.

Dongmei Zhu, Junyu Li, Yan Li, Ji Wu, Lin Zhu, Jian Li, Zimo Wang, Jinfeng Xu, Fajin Dong, Jun Cheng

Abstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. An interpretable machine learning model for preoperative prediction of renal mass malignancy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
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.

Dongmei ZhuDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen, China.
Junyu LiNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
Yan LiDepartment of Ultrasound, The Affiliated Nanchong Central Hospital of North Sichuan Medical College, Nanchong, China.
Ji WuDepartment of Urology Surgery, The Affiliated Nanchong Central Hospital of North Sichuan Medical College, Nanchong, China.
Lin ZhuDepartment of Ultrasound, The Affiliated Nanchong Central Hospital of North Sichuan Medical College, Nanchong, China.
Jian LiDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen, China.
Zimo WangDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen, China.
Jinfeng XuDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen, China.
Fajin DongDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen, China.
Jun ChengNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial intelligenceclassificationcontrast-enhanced ultrasounddeep learningrenal tumor

Identifiers

PMID36148014
PMCPMC9488515

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.