Evidence map›Paper›PMID 38730045›Full record

ArticleScientific reports2024

Classification performance assessment for imbalanced multiclass data.

Jesús S Aguilar-Ruiz, Marcin Michalak

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Quality Assurance Strategies for Brain State Characterization by MEMRI.bioRxiv : the preprint server for biology · 2026
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. 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

2 authors.

Jesús S Aguilar-Ruiz *School of Engineering, Pablo de Olavide University, 41013, Seville, Spain. aguilar@upo.es.
Marcin Michalak *Department of Computer Networks and Systems, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.

Funding

Department of Computer Networks and Systems, Silesian University of Technology RAu9MCIN/AEI/10.13039/ 501100011033, the Andalusian Plan for Research, Development and Innovation PID2020-117759GB-I00
6 · The paper itself

Abstract

The evaluation of diagnostic systems is pivotal for ensuring the deployment of high-quality solutions, especially given the pronounced context-sensitivity of certain systems, particularly in fields such as biomedicine. Of notable importance are predictive models where the target variable can encompass multiple values (multiclass), especially when these classes exhibit substantial frequency disparities (imbalance). In this study, we introduce the Imbalanced Multiclass Classification Performance (IMCP) curve, specifically designed for multiclass datasets (unlike the ROC curve), and characterized by its resilience to class distribution variations (in contrast to accuracy or F

Indexed as

NeoplasmsAlgorithmsHumansROC Curve

Identifiers

PMID38730045
PMCPMC11087593

What OpenQuestion holds

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Registered trials

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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.