ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2401.10291
  4. Cited By
Detecting Post-Stroke Aphasia Via Brain Responses to Speech in a Deep
  Learning Framework

Detecting Post-Stroke Aphasia Via Brain Responses to Speech in a Deep Learning Framework

17 January 2024
Pieter De Clercq
Corentin Puffay
J. Kries
Hugo Van hamme
M. Vandermosten
T. Francart
Jonas Vanthornhout
ArXivPDFHTML

Papers citing "Detecting Post-Stroke Aphasia Via Brain Responses to Speech in a Deep Learning Framework"

4 / 4 papers shown
Title
Detecting post-stroke aphasia using EEG-based neural envelope tracking
  of natural speech
Detecting post-stroke aphasia using EEG-based neural envelope tracking of natural speech
Pieter De Clercq
J. Kries
R. Mehraram
Jonas Vanthornhout
T. Francart
M. Vandermosten
36
6
0
14 Mar 2023
Relating EEG to continuous speech using deep neural networks: a review
Relating EEG to continuous speech using deep neural networks: a review
Corentin Puffay
Bernd Accou
Lies Bollens
Mohammad Jalilpour-Monesi
Jonas Vanthornhout
Hugo Van hamme
T. Francart
57
41
0
03 Feb 2023
Predicting speech intelligibility from EEG in a non-linear
  classification paradigm
Predicting speech intelligibility from EEG in a non-linear classification paradigm
Bernd Accou
Mohammad Jalilpour-Monesi
Hugo Van hamme
T. Francart
16
12
0
14 May 2021
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
800
21,760
0
22 May 2017
1