Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a narrative review

BACKGROUND AND OBJECTIVE: Machine learning (ML) models are increasingly being utilized in oncology research for use in the clinic. However, while more complicated models may provide improvements in predictive or prognostic power, a hurdle to their adoption are limits of model interpretability, where...

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Detalles Bibliográficos
Autores principales: Ladbury, Colton, Zarinshenas, Reza, Semwal, Hemal, Tam, Andrew, Vaidehi, Nagarajan, Rodin, Andrei S., Liu, An, Glaser, Scott, Salgia, Ravi, Amini, Arya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Review Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641128/
https://www.ncbi.nlm.nih.gov/pubmed/36388027
http://dx.doi.org/10.21037/tcr-22-1626

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641128/
https://www.ncbi.nlm.nih.gov/pubmed/36388027
http://dx.doi.org/10.21037/tcr-22-1626

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