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Evidence record 18324 · automatically gathered

Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability

Parkinson's disease (PD) is the second most common neurodegenerative disorder. Typical machine learning screening methods require PD labels, but the available data is limited by privacy concerns and the need for expert annotation. We propose a label-free face-plus-voice PD screen built entirely on frozen pretrained encoders--a face-expression Vision Transformer and HuBERT--in which no PD label touches any fit; the reference is training controls only. The voice modality uses a synthetic-dysarthri

Record details

Published: 10 August 2026
Source: arXiv cs.LG
Category: Research
Topics: Safety & alignment · Privacy
Retrieved: 11 August 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (10 August 2026), “Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability,” evidence record 18324, https://ethics.ai/record/18324 (originally published by arXiv cs.LG).

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