Evidence map›Paper›PMID 40479183›Full record

ArticleAnnals of data science2022

An Improved K-means Clustering Algorithm Towards an Efficient Data-Driven Modeling.

Md Zubair, Md Asif Iqbal, Avijeet Shil, M J M Chowdhury, Mohammad Ali Moni, Iqbal H Sarker

Abstract read
In one paragraph

Article in Annals of data science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Revealing chronic disease progression patterns using Gaussian process for stage inference.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  13. Article
  14. Article
  15. 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

6 authors.

Md ZubairDepartment of Computer Science and Engineering, Chittagong University of Engineering & Technology, Chittagong, 4349 Bangladesh.
Md Asif IqbalDepartment of Computer Science and Engineering, Chittagong University of Engineering & Technology, Chittagong, 4349 Bangladesh.
Avijeet ShilDepartment of Computer Science and Engineering, Chittagong University of Engineering & Technology, Chittagong, 4349 Bangladesh.
M J M ChowdhuryDepartment of Computer Science and Information Technology, La Trobe University, Victoria, 3086 Australia.
Mohammad Ali MoniSchool of Health and Rehabilitation Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, St Lucia, QLD 4072 Australia.
Iqbal H SarkerDepartment of Computer Science and Engineering, Chittagong University of Engineering & Technology, Chittagong, 4349 Bangladesh.ORCID 0000-0003-1740-5517

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

K-means algorithm is one of the well-known unsupervised machine learning algorithms. The algorithm typically finds out distinct non-overlapping clusters in which each point is assigned to a group. The minimum squared distance technique distributes each point to the nearest clusters or subgroups. One of the K-means algorithm's main concerns is to find out the

Indexed as

Data ScienceK-means ClusteringMachine LearningPercentilePrincipal Component AnalysisUnsupervised Algorithm

Identifiers

PMID40479183
PMCPMC9243813

What OpenQuestion holds

Textmetadata
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.