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Article

A machine learning approach based on ACMG/AMP guidelines for genomic variant classification and prioritization.

Scientific reports - 15 Feb 2022

Nicora Giovanna, Zucca Susanna, Limongelli Ivan, Bellazzi Riccardo, Magni Paolo

Abstract excerpt

Genomic variant interpretation is a critical step of the diagnostic procedure, often supported by the application of tools that may predict the damaging impact of each variant or provide a guidelines-based classification. We propose the application of Machine Learning methodologies, in particular Penalized Logistic Regression, to support variant classification and prioritization. Our approach combines ACMG/AMP...

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Identifiers

PMID: 35169226
DOI: 10.1038/s41598-022-06547-3
PMCID: PMC8847497

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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