A Computational Audit of Demographic Association Encoding in ClinicalBERT Language Predictions
Transformer-based clinical language models are increasingly integrated into high-stakes clinical decision support pipelines, yet the computational mechanisms through which demographic associations encoded in medical documentation propagate into model probability distributions remain empirically underspecified. We present a systematic computational audit of representational bias in ClinicalBERT (Alsentzer et al., 2019), a BERT-based model pretrained on MIMIC-III discharge summaries, employing two complementary probing methodologies: Log Probability Bias Analysis (LPBA), which quantifies demographic descriptor-induced shifts in masked token probability distributions across behavioral and ev...
| Authors | Kehinde Temitayo Soetan |
|---|---|
| Primary category | cs.CL |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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