arXiv AI

Gated Multi-Graph Fusion via Graph Attention Networks for Alzheimer's Disease Detection

arXiv:2606. 31186v1 Announce Type: cross Abstract: Spontaneous speech is a vital non-invasive biomarker for Alzheimer's Disease (AD), yet many systems overlook non-linear structural disruptions and clinical heterogeneity in pathological language.

arXiv AI

Jul 1

Listening Between the Lines: Joint Learning of ASR Embeddings and LLM-Augmented Linguistics for Dementia Detection

arXiv:2606. 30675v1 Announce Type: cross Abstract: Early detection of dementia through speech analysis offers a non-invasive screening alternative, but capturing both acoustic and linguistic biomarkers remains challenging.

By Olivier Jiyoun Jung, Jonghyeon Park, Myungwoo Oh

llms rag multimodal benchmarks

arXiv AI

Jun 3

Multi-Modal Graph Neural Network with Transformer-Guided Adaptive Diffusion for Preclinical Alzheimer Classification

arXiv:2606. 03322v1 Announce Type: cross Abstract: The graphical representation of the brain offers critical insights into diagnosing and prognosing neurodegenerative disease via relationships between regions of interest (ROIs).

By Jaeyoon Sim, Minjae Lee, Guorong Wu, Won Hwa Kim

llms diffusion multimodal

arXiv AI

Jul 1

ASR-Agnostic Multimodal Spectrotemporal Modeling for Early Dementia Detection

arXiv:2606. 30646v1 Announce Type: cross Abstract: Speech recruits the same executive, attentional, and working memory processes underlying instrumental activities of daily living, or IADLs, providing a non-invasive proxy for cognitive assessment.

By Chukwuemeka Ugwu, Oluwafemi Richard Oyeleke

llms rag multimodal benchmarks

arXiv AI

Jul 3

SABER: A Semantic-Aligned Brain Network Analysis Framework via Multi-scale Hypergraphs

arXiv:2607. 01901v1 Announce Type: cross Abstract: Effective brain disease diagnosis requires the synergy of brain connectivity patterns and high-level semantic knowledge.

By Yidan Xu, Xiangmin Han, Rundong Xue, Huihui Ye

llms rag benchmarks safety

arXiv Machine Learning

Aug 5

PatTree: a novel approach for automated creation of multimodal, graph-based patient representations for medical classification tasks

arXiv:2608. 02692v1 Announce Type: new Abstract: Access to holistic, multimodal data improves the performance of Artificial Intelligence (AI) in medical classification tasks compared to utilizing single modalities or data sources.

By Julia Gehrmann, Lars Quakulinski, Hamza Naseem, Oya Beyan

multimodal benchmarks

arXiv Machine Learning

Jul 14

MVMGNN;Multi-View Masked Graph Neural Network for Alzheimer's Disease Diagnosis using Structural MRI

arXiv:2607. 09788v1 Announce Type: cross Abstract: Alzheimer's disease (AD) is a common neurodegenerative disorder, and early diagnosis is of great significance for delaying disease progression and enabling timely intervention.

By Ni Yao, Zhenxu Wang, Danyang Sun, Chuang Han, Yanting Li, Jiaofen Nan, Fubao Zhu, Chen Zhao, Weihua Zhou

safety

arXiv Machine Learning

Jul 24

Toward Generalizable Cognitive Impairment Detection with Speech-Based Multimodal Large Language Models

arXiv:2607. 21496v1 Announce Type: cross Abstract: Cognitive impairment (CI) is a growing public health concern.

By Yingchao Huang, Xin Wang, Yuhan Su, Shanshan Yao

llms rag multimodal benchmarks safety

arXiv Machine Learning

Aug 3

A Neurosymbolic Approach for Explainable Early Diagnosis of Alzheimer's Disease

arXiv:2607. 29530v1 Announce Type: new Abstract: Identifying reliable Alzheimer's disease (AD) markers typically requires manual, labor-intensive transcription and expert analysis, limiting its scale.

By Ranveer Singh, Pranuthi Tenali, Saurabh Mathur, Ameet Soni, Vaishali Phatak, Karla Lynch, Daniel Murman, Matthew Rizzo, Sriraam Natarajan

arXiv AI

Jul 14

Transcript-Free Lightweight Detection of Alzheimer's Disease from Spontaneous Speech Using Handcrafted MFCC-Dominant Acoustic Biomarkers

arXiv:2607. 10168v1 Announce Type: cross Abstract: It is still hard to find Alzheimer's disease (AD) early, especially when neuroimaging is expensive or tools that depend on language are not available.

By Rashin Gholijani Farahani, Azam Bastanfard

multimodal

arXiv AI

Jun 30

LoRA-Tuned Large Language Models for Dementia Detection via Multi-View Speech-Derived Features

arXiv:2606. 28445v1 Announce Type: cross Abstract: Early detection of dementia enables timely intervention, and reflecting cognitive impairment, spontaneous speech offers a non-invasive screening modality.

By Jonghyeon Park, Olivier Jiyoun Jung, Myungwoo Oh

llms fine-tuning multimodal benchmarks

arXiv Machine Learning

Jun 9

Multi-View Speech Representation Learning for Parkinson's Disease Detection Using Context-guided Cross-modal Attention

arXiv:2606. 09271v1 Announce Type: cross Abstract: Parkinson's disease (PD) is a progressive neurodegenerative disorder that frequently causes speech impairments associated with hypokinetic dysarthria.

By George Theodosiou, Loukas Ilias, Dimitris Askounis

rag multimodal benchmarks

arXiv AI

Jun 17

SpeechDx: A Multi-Task Benchmark for Clinical Speech AI

arXiv:2606. 17339v1 Announce Type: new Abstract: Speech offers a uniquely informative window into health by simultaneously engaging neurological, motor, respiratory, and vocal systems.

By Sejal Bhalla, Larry Kieu, Aina Merchant, Eyal de Lara, Alex Mariakakis

benchmarks

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