Evidence map›Paper›PMID 34960509›Full record

ReviewSensors (Basel, Switzerland)2021

A Survey of Methods and Technologies Used for Diagnosis of Scoliosis.

Ilona Karpiel, Adam Ziębiński, Marek Kluszczyński, Daniel Feige

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 18% 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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. A fully automatic Cobb angle measurement framework of full-spine DR images based on deep learning.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025
    Article
  8. Artificial Intelligence-Based Large Language Models Can Facilitate Patient Education.Journal of the Pediatric Orthopaedic Society of North America · 2025
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. 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

4 authors at 3 institutions in 1 country.

Ilona KarpielŁukasiewicz Research Network-Institute of Medical Technology and Equipment, 118 Roosevelt, 41-800 Zabrze, Poland.ORCID 0000-0002-2104-7997
Adam ZiębińskiDepartment of Distributed Systems and Informatic Devices, Silesian University of Technology, 16 Akademicka, 44-100 Gliwice, Poland.ORCID 0000-0003-4554-6667
Marek KluszczyńskiDepartment of Health Sciences, Jan Dlugosz University, 4/8 Waszyngtona, 42-200 Częstochowa, Poland.ORCID 0000-0002-3187-9279
Daniel FeigeŁukasiewicz Research Network-Institute of Medical Technology and Equipment, 118 Roosevelt, 41-800 Zabrze, Poland.ORCID 0000-0001-6840-0965
Silesian University of Technology · PLInstitute of Medical Technology and Equipment · PLJan Długosz University · PL

Funding

Ministry of Science and Higher Education DWD/3/7/2019
6 · The paper itself

Abstract

The purpose of this article is to present diagnostic methods used in the diagnosis of scoliosis in the form of a brief review. This article aims to point out the advantages of select methods. This article focuses on general issues without elaborating on problems strictly related to physiotherapy and treatment methods, which may be the subject of further discussions. By outlining and categorizing each method, we summarize relevant publications that may not only help introduce other researchers to the field but also be a valuable source for studying existing methods, developing new ones or choosing evaluation strategies.

Indexed as

ScoliosisHumansSpineSurveys and Questionnairesartificial intelligence diagnosiscomputer analysisdiagnostic imagingscoliosisspinal curvaturesspine

Identifiers

PMID34960509
PMCPMC8707023
OpenAlexW4200598238

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.