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Article

Balancing complexity and clarity-towards clinician-ready antibiotic resistance prediction models.

Bioinformatics (Oxford, England) - 2 Oct 2025

Aruhomukama Dickson

Abstract excerpt

MOTIVATION: The escalating challenge of antibiotic resistance (ABR) demands clinician-ready machine learning models that are not only accurate but interpretable. RESULTS: By treating resistance genes as independent features and augmenting them with curated single-nucleotide polymorphisms and contextual markers, this approach delivers scalable, transparent predictions aligned with clinical decision-making needs....

Read the complete abstract on PubMed

Topics

Machine Learning
Polymorphism, Single Nucleotide
Humans
Drug Resistance, Microbial
Anti-Bacterial Agents
Drug Resistance, Bacterial

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Computational Biology

Source

Open in PubMed Open full text

Identifiers

PMID: 41032281
DOI: 10.1093/bioinformatics/btaf556
PMCID: PMC12518920

Genes

ABR

Provenance

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