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Article

Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions.

Artificial intelligence in medicine - 1 Aug 2022

Prosperi Mattia, Boucher Christina, Bian Jiang, Marini Simone

Abstract excerpt

Whole genome sequencing (WGS) is quickly becoming the customary means for identification of antimicrobial resistance (AMR) due to its ability to obtain high resolution information about the genes and mechanisms that are causing resistance and driving pathogen mobility. By contrast, traditional phenotypic (antibiogram) testing cannot easily elucidate such information. Yet development of AMR prediction tools from...

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Identifiers

PMID: 35809965
DOI: 10.1016/j.artmed.2022.102326
PMCID: PMC9425730

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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