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Mitigating Algorithmic Bias in Cancer Site Classification Models
0
Zitationen
6
Autoren
2026
Jahr
Abstract
Our findings demonstrate that HiSAN-generated embeddings from SEER data can be used effectively in cancer site classification without significant demographic bias influencing the outcomes. Post-training pruning therefore functions as a practical audit and sensitivity check.
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