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...
| Published in: | Journal of Digital Imaging Vol. 35; no. 5; pp. 1164 - 1176 |
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| Main Authors: | , , , |
| Format: | diagnostic images pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Oct2022
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| Online Access: | View this record in EBSCOhost |