AI Virtual Patients in Audiology Education: Student and Educator Perspectives

PubMed·Journal article·AI & technology·1d ago

A systematic review of machine learning techniques for real-time speech and noise classification in hearing aids

No immediate practice change warranted, but audiologists should monitor this fast-moving area as ML-based classifiers are approaching real-time clinical deployment and may soon influence device selection counseling.

PU

PubMed·Journal article·AI & technology·3d ago

Real-time brain-controlled selective hearing enhances speech perception in multi-talker environments

This is a promising proof-of-concept, but the technology requires real-time neural decoding hardware not yet suitable for clinical hearing aids; no practice change is warranted now, though audiologists should monitor this research area closely.

PU

PubMed·Journal article·AI & technology·6d ago

ASEAF: Attention-SincNet driven EEG-audio fused target speaker extraction network

EEG-audio fused auditory attention decoding represents a key research frontier for next-generation neuro-steered hearing aids, making this directly relevant to audiology's technology pipeline.

PU

PubMed·Journal article·AI & technology·8d ago

In-ear EEG wearables for brain activity assessment and cognitive rehabilitation: the emerging role of multimodal embedded intelligence

In-ear EEG wearables represent a convergence of audiology hardware and neurotechnology that could reshape how hearing devices are designed and what cognitive services audiologists provide.

ASHA Voices·Podcast·AI & technology·2y ago

How AI Can Aid Care Coordination for Patients Experiencing Dizziness

Audiologist Devin McCaslin (University of Michigan) discusses his work using AI to streamline care coordination and reduce costs for patients experiencing dizziness and balance disorders.

PU

PubMed·Journal article·AI & technology·2w ago

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