Artificial Intelligence in Human Genetics

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Authors: Nadav Brandes
Cited by: 0
References: 80

Abstract

Artificial intelligence (AI) technologies have recently undergone transformative growth in capabilities. In human genetics, AI is rapidly advancing our ability to reveal the effects of genetic variation. This review explores recent progress and remaining challenges across the diverse applications of AI in genotype-to-phenotype mapping, from predicting the functional and clinical consequences of mutations, to identifying causal genes, to estimating disease risk. Particular emphasis is placed on the growing utility of general-purpose foundation models trained on massive genomic data, including DNA and protein language models, alongside areas where narrower machine-learning approaches still dominate. The review concludes with key considerations for future progress and impact.

Fields of Study & Subjects

Genomics and Rare Diseases Genetic Associations and Epidemiology Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Annual Review of Genomics and Human Genetics
Volume
27
Issue
1
Pages
183–204
Publication date
25 February 2026
Language
EN