High-dimensional biomarker identification for interpretable disease prediction via machine learning models

Authors

Ian M. Carroll (ORCID: https://orcid.org/0000-0001-8615-5086)
Baiming Zou (ORCID: https://orcid.org/0000-0002-7879-9460)
Fei Zou (ORCID: https://orcid.org/0000-0002-6637-3593)
Di Wu (ORCID: https://orcid.org/0000-0001-8331-2357)
Yifan Dai (ORCID: https://orcid.org/0000-0001-7897-5228)

Institutions

University of North Carolina at Chapel Hill (US)

Publication Details

Journal: Bioinformatics
Published: 2025-04-25
DOI: https://doi.org/10.1093/bioinformatics/btaf266
Citations: 3
Primary Topic: Genetic Associations and Epidemiology
Type: article
Field-Weighted Citation Impact: 5.45

Funders

National Institutes of Health

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article

High-dimensional biomarker identification for interpretable disease prediction via machine learning models

Ian M. Carroll, Baiming Zou, Fei Zou, Di Wu et al.

Apr 25, 2025

3 citations

Bioinformatics

Genetic Associations and Epidemiology

5.45

article

High-dimensional biomarker identification for interpretable disease prediction via machine learning models

Ian M. Carroll, Baiming Zou, Fei Zou, Di Wu, Yifan Dai

April 25, 2025article en

3 citations

Abstract

No abstract available for this paper.

BioinformaticsVol. 41(5)

University of North Carolina at Chapel Hill (US)

National Institutes of Health

Openalex Percentile: Top 5%

Genetic Associations and Epidemiology

5.45

DOI Open Access PDF OpenAlex

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High-dimensional biomarker identification for interpretable disease prediction via machine learning models — Ian M. Carroll, Baiming Zou, et al. · Bioinformatics (2025) | TGRS Research Map | TGRS