Evidence map›Paper›PMID 36982012›Full record

ArticleInternational journal of environmental research and public health2023

Intelligent Fuzzy System to Predict the Wisconsin Breast Cancer Dataset.

Yamid Fabián Hernández-Julio, Leonardo Antonio Díaz-Pertuz, Martha Janeth Prieto-Guevara, Mauricio Andrés Barrios-Barrios, Wilson Nieto-Bernal

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Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Enhancing breast cancer treatment selection through 2TLIVFrontiers in artificial intelligence · 2024
    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

5 authors.

Yamid Fabián Hernández-JulioFaculty of Economics, Administrative and Accounting Sciences, Universidad del Sinú Elías Bechara Zainúm, Montería 230002, Colombia.ORCID 0000-0002-0129-1837
Leonardo Antonio Díaz-PertuzFaculty of Economics, Administrative and Accounting Sciences, Universidad del Sinú Elías Bechara Zainúm, Montería 230002, Colombia.
Martha Janeth Prieto-GuevaraDepartamento de Ciencias Acuícolas-Medicina Veterinaria y Zootecnia (CINPIC), Universidad de Córdoba, Montería 230002, Colombia.ORCID 0000-0003-3458-4983
Mauricio Andrés Barrios-BarriosSystems Engineering Department, Universidad de la Costa, Barranquilla 080001, Colombia.ORCID 0000-0002-1933-8496
Wilson Nieto-BernalFacultad de Ingeniería, Departamento de Ingeniería de Sistemas, Universidad del Norte, Barranquilla 80001, Colombia.ORCID 0000-0003-3615-4629

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Decision Support Systems (DSSs) are solutions that serve decision-makers in their decision-making process. For the development of these intelligent systems, two primary components are needed: the knowledge database and the knowledge rule base. The objective of this research work was to implement and validate diverse clinical decision support systems supported by Mamdani-type fuzzy set theory using clustering and dynamic tables. The outcomes were evaluated with other works obtained from the literature to validate the suggested fuzzy systems for categorizing the Wisconsin breast cancer dataset. The fuzzy Inference Systems worked with different input features, according to the studies obtained from the literature. The outcomes confirm that most performance' metrics in several cases were greater than the achieved results from the literature for the output variable for the different Fuzzy Inference Systems-FIS, demonstrating superior precision.

Indexed as

Breast NeoplasmsDecision Support Systems, ClinicalFemaleFuzzy LogicHumansKnowledge BasesWisconsinbreast cancerclustersfuzzy systempivot tables

Identifiers

PMID36982012
PMCPMC10049073

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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.