An interpretable deep learning framework based on time–frequency analysis for automated auditory brainstem response detection

doi:10.1016/j.bspc.2025.108609

An interpretable deep learning framework based on time–frequency analysis for automated auditory brainstem response detection

2025-08-20

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DOI：10.1016/j.bspc.2025.108609

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Abstract

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• A novel and interpretable model for automated ABR detection. • Combination of time–frequency analysis and Vision Transformer. • Evaluated on large and diverse clinical datasets from different centers. • Proposed two visualization methods for ABR detection based on Grad-CAM and SHAP.

Keywords:

ABR detection

time-frequency analysis

Vision Transformer

Grad-CAM

SHAP

An interpretable deep learning framework based on time–frequency analysis for automated auditory brainstem response detection

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