Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare

Cirillo, Davide; Catuara‐Solarz, Silvina; Morey, Czuee; Güney, Emre; Subirats, Laia; Mellino, Simona; Gigante, Annalisa; Valencia, Alfonso; Rementeria, María José; Chadha, Antonella Santuccione; Mavridis, Nikolaos

doi:10.1038/s41746-020-0288-5

reviewnpj Digital MedicineJun 1, 2020GOLD OA

Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare

DCDavide Cirillo SCSilvina Catuara‐Solarz CMCzuee Morey EGEmre Güney LSLaia Subirats

Barcelona Supercomputing Center · Universitat Politècnica de Catalunya · +8 more institutions

PubMed

Indexed incrossrefdoajpubmed

Abstract

Precision Medicine implies a deep understanding of inter-individual differences in health and disease that are due to genetic and environmental factors. To acquire such understanding there is a need for the implementation of different types of technologies based on artificial intelligence (AI) that enable the identification of biomedically relevant patterns, facilitating progress towards individually tailored preventative and therapeutic interventions. Despite the significant scientific advances achieved so far, most of the currently used biomedical AI technologies do not account for bias detection. Furthermore, the design of the majority of algorithms ignore the sex and gender dimension and its contribution…

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Topics & keywords

Topics

Keywords

Biomedicine
Precision medicine
Identification (biology)
Psychological intervention
Disease
Dimension (graph theory)
Artificial intelligence
Relation (database)

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