Evidence map›Paper›PMID 40292490›Full record

ArticleNutrients2025

Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection.

Guadalupe Gutiérrez-Esparza, Mireya Martínez-García, Manlio F Márquez-Murillo, Malinalli Brianza-Padilla, Enrique Hernández-Lemus, Luis M Amezcua-Guerra

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nutrients, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Guadalupe Gutiérrez-Esparza"Researcher for Mexico" Program under SECIHTI, Secretariat of Sciences, Humanities, Technology, and Innovation, Mexico City 08400, Mexico.
Mireya Martínez-GarcíaDepartment of Immunology, National Institute of Cardiology Ignacio Chávez, Mexico City 04510, Mexico.ORCID 0000-0002-2876-8500
Manlio F Márquez-MurilloDivision of Diagnostic and Treatment Services, National Institute of Cardiology Ignacio Chávez, Mexico City 04510, Mexico.ORCID 0000-0001-7294-7330
Malinalli Brianza-PadillaDepartment of Immunology, National Institute of Cardiology Ignacio Chávez, Mexico City 04510, Mexico.
Enrique Hernández-LemusComputational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.ORCID 0000-0002-1872-1397
Luis M Amezcua-GuerraDepartment of Immunology, National Institute of Cardiology Ignacio Chávez, Mexico City 04510, Mexico.ORCID 0000-0002-6258-5732

Funding

CONAHCYT 1591
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

HyperuricemiaMachine LearningUric AcidAdultAgedBiomarkersCohort StudiesFemaleHumansLife StyleMaleMexicoMiddle AgedRisk FactorsBiomarkersUric Acidfeature engineeringfeature selectionMexico Cityregression-based machine learningTlalpan 2020 cohorturic acid

Identifiers

PMID40292490
PMCPMC11946391

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.