Using Occlusion-Based Saliency Maps to Explain an Artificial Intelligence Tool in Lung Cancer Screening: Agreement Between Radiologists, Labels, and Visual Prompts

Occlusion-based saliency maps (OBSMs) are one of the approaches for interpreting decision-making process of an artificial intelligence (AI) system. This study explores the agreement among text responses from a cohort of radiologists to describe diagnostically relevant areas on low-dose CT (LDCT) ima...

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Detalles Bibliográficos
Autores principales: Gandomkar, Ziba, Khong, Pek Lan, Punch, Amanda, Lewis, Sarah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582174/
https://www.ncbi.nlm.nih.gov/pubmed/35484439
http://dx.doi.org/10.1007/s10278-022-00631-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582174/
https://www.ncbi.nlm.nih.gov/pubmed/35484439
http://dx.doi.org/10.1007/s10278-022-00631-w

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