Classification of Alzheimer's Disease with Deep Learning on Eye-tracking Data-Reference-Cited by-同舟云学术

Classification of Alzheimer's Disease with Deep Learning on Eye-tracking Data

Published:2023-10-09 Issue: Volume: Page:
ISSN:
Container-title:INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION
language:
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Author:

Sriram Harshinee¹^ORCID,Conati Cristina¹^ORCID,Field Thalia²^ORCID

Affiliation:

1. Department of Computer Science, The University of British Columbia, Canada

2. Vancouver Stroke Program and Division of Neurology, Faculty of Medicine, The University of British Columbia, Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3577190.3614149

Reference57 articles.

1. Sarker Monojit Asish , Arun K. Kulshreshth , and Christoph W . Borst . 2022 . Detecting distracted students in educational VR environments using machine learning on eye gaze data. Computers & Graphics 109, (December 2022), 75–87. DOI:https://doi.org/10.1016/j.cag.2022.10.007 10.1016/j.cag.2022.10.007 Sarker Monojit Asish, Arun K. Kulshreshth, and Christoph W. Borst. 2022. Detecting distracted students in educational VR environments using machine learning on eye gaze data. Computers & Graphics 109, (December 2022), 75–87. DOI:https://doi.org/10.1016/j.cag.2022.10.007

2. Mohammad Ehsan Basiri , Shahla Nemati , Moloud Abdar , Erik Cambria , and U. Rajendra Acharya . 2021 . ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis. Future Generation Computer Systems 115, (February 2021), 279–294. DOI:https://doi.org/10.1016/j.future.2020.08.005 10.1016/j.future.2020.08.005 Mohammad Ehsan Basiri, Shahla Nemati, Moloud Abdar, Erik Cambria, and U. Rajendra Acharya. 2021. ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis. Future Generation Computer Systems 115, (February 2021), 279–294. DOI:https://doi.org/10.1016/j.future.2020.08.005

3. Juan Biondi Gerardo Fernandez Silvia Castro and Osvaldo Agamennoni. 2018. Eye-Movement behavior identification for AD diagnosis. DOI:https://doi.org/10.48550/arXiv.1702.00837 10.48550/arXiv.1702.00837

4. Juan Biondi Gerardo Fernandez Silvia Castro and Osvaldo Agamennoni. 2018. Eye-Movement behavior identification for AD diagnosis. DOI:https://doi.org/10.48550/arXiv.1702.00837

5. Robert Bixler and Sidney D'Mello . 2015. Automatic Gaze-Based Detection of Mind Wandering with Metacognitive Awareness . In User Modeling, Adaptation and Personalization (Lecture Notes in Computer Science) , Springer International Publishing , Cham , 31–43. DOI:https://doi.org/10.1007/978-3-319-20267-9_3 10.1007/978-3-319-20267-9_3 Robert Bixler and Sidney D'Mello. 2015. Automatic Gaze-Based Detection of Mind Wandering with Metacognitive Awareness. In User Modeling, Adaptation and Personalization (Lecture Notes in Computer Science), Springer International Publishing, Cham, 31–43. DOI:https://doi.org/10.1007/978-3-319-20267-9_3

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