arXiv Machine Learning By Liu He, Yuanchao Li, Yin-Long Liu, Rui Feng, Yiming Wang, Jiaxin Chen, Yizhe Wang, Jiahong Yuan

Disentangling Acoustic Cues in Alzheimer's Pathology and Perception: The Roles of Language and Gender

Read the original on arXiv Machine Learning →

arXiv:2607. 23977v1 Announce Type: cross Abstract: Acoustic biomarkers show promise for detecting Alzheimer's Disease (AD), yet whether the cues driving diagnostic AI align with those salient to human listeners is underexplored across languages and genders, where pathological markers and perceptual strategies differ.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jun 2

A Monosemantic Attribution Framework for Stable Interpretability in Clinical Neuroscience Transformer-Based Language Models

arXiv:2601. 17952v2 Announce Type: replace-cross Abstract: Interpretability remains a key challenge for deploying language models (LM) in clinical settings such as progression diagnosis of Alzheimer disease, where early and trustworthy predictions are essential.

By Michail Mamalakis, Tiago Azevedo, Cristian Cosentino, Chiara D'Ercoli, Subati Abulikemu, Zhongtian Sun, Richard Bethlehem, Pietro Lio