Evidence map›Paper›PMID 34759797›Full record

ArticleFrontiers in neuroscience2021

Kernelized

Xiaobin Liu, Xiran Zhang, Yi Zhang, Yijie Ding, Weiwei Shan, Yiqing Huang, Liang Wang, Xiaoyi Guo

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 4 institutions in 1 country.

Xiaobin LiuDepartment of Nephrology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Xiran ZhangDepartment of Nephrology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Yi ZhangNHC Key Laboratory of Nuclear Medicine, Jiangsu Key Laboratory of Molecular Nuclear Medicine, Jiangsu Institute of Nuclear Medicine, Wuxi, China.
Yijie DingYangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.
Weiwei ShanDepartment of Nephrology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Yiqing HuangDepartment of Nephrology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Liang WangDepartment of Nephrology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Xiaoyi GuoInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China.
Nanjing Medical University · CNKey Laboratory of Nuclear Radiation and Nuclear Energy Technology · CNQuzhou University · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detecting and treating cerebrovascular diseases are essential for the survival of patients with chronic kidney disease (CKD). Machine learning algorithms can be used to effectively predict stroke risk in patients with end-stage renal disease (ESRD). An imbalance in the amount of collected data associated with different risk levels can influence the classification task. Therefore, we propose the use of a kernelized

Indexed as

cerebrovascular diseaseend-stage renal diseaseFGF23klotholocal hyperplane

Identifiers

PMID34759797
PMCPMC8573245
OpenAlexW3211080148

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.