- The language of the eyes
Diane Haynes, Frontiers of Medicine, TREK Magazine for UBC Alumni, June 16, 2021. The following is an article from the UBC Alumni TREK Magazine. You can read the full article here. Bicycle, velvet, church. I watch over her shoulder… Read more: The language of the eyes - Exploring neural models for predicting dementia from language
Weirui Kong, Hyeju Jang, Giuseppe Carenini, Thalia S. Field, Computer Speech & Language, Volume 68, 2021, 101181, ISSN 0885-2308, Early prediction of neurodegenerative disorders such as Alzheimer’s disease (AD) and related dementias may facilitate earlier access to medical… Read more: Exploring neural models for predicting dementia from language - Machine learning analysis of speech and eye tracking data to distinguish Alzheimer’s clinic patients from healthy controls
Thalia S. Field, Sally May Newton-Mason, Sheetal Shajan, Oswald Barral, Hyeju Jang, Thomas Soroski, Zoe O’Neill, Cristina Conati, Giuseppe Carenini, Alzheimer’s Dement. 2020;16(Suppl. 5):e046742. Background: Clinical trials of disease-modifying therapies for Alzheimer’s disease (AD) are increasingly focused on… Read more: Machine learning analysis of speech and eye tracking data to distinguish Alzheimer’s clinic patients from healthy controls - Non-Invasive Classification of Alzheimer’s Disease Using Eye-Tracking and Language
Oswald Barral, Hyeju Jang, Sally Newton-Mason, Sheetal Shajan, Thomas Soroski, Giuseppe Carenini, Cristina Conati, Thalia Field, Proceedings of the 5th Machine Learning for Healthcare Conference, PMLR 126:813-841, 2020. Alzheimer’s disease (AD) is an insidious progressive neurodegenerative disease resulting… Read more: Non-Invasive Classification of Alzheimer’s Disease Using Eye-Tracking and Language - Leveraging eye tracking and spontaneous speech data to improve reliable detection of Alzheimer’s Disease.
Oswald Barral, Giuseppe Carenini, Cristina Conati, Thalia S. Field, Zoe O’Neill and Tom Soroski, 3RD WORKSHOP ON AI FOR AGING, REHABILITATION AND INDEPENDENT ASSISTED LIVING (ARIAL) @IJCAI’19, 10-12 AUGUST This paper presents a novel approach to investigate the… Read more: Leveraging eye tracking and spontaneous speech data to improve reliable detection of Alzheimer’s Disease. - A Neural Model for Predicting Dementia from LanguageWeirui Kong, Hyeju Jang, Giuseppe Carenini, Thalia Field; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:270-286, 2019. Early prediction of neurodegenerative disorders such as Alzheimer’s disease (AD) and related dementias is important in developing early medical supports and social supports, and… Read more: A Neural Model for Predicting Dementia from Language
- Detecting Dementia through Retrospective Analysis of Routine Blog Posts by Bloggers with Dementia
Vaden Masrani, Gabriel Murray, Thalia Field, Giuseppe Carenini, 2017. BioNLP Association for Computational Linguistics, p. 232-237 We investigate if writers with dementia can be automatically distinguished from those without by analyzing linguistic markers in written text, in the form of blog… Read more: Detecting Dementia through Retrospective Analysis of Routine Blog Posts by Bloggers with Dementia - Domain Adaptation for Detecting Mild Cognitive Impairment
Vaden Masrani, Gabriel Murray, Thalia Shoshana Field, and Giuseppe Carenini, Canadian AI 2017: Advances in Artificial Intelligence pp 248-259. Lexical and acoustic markers in spoken language can be used to detect mild cognitive impairment (MCI), a condition which is often… Read more: Domain Adaptation for Detecting Mild Cognitive Impairment