Digital detection of Alzheimer's disease using smiles and conversations with a chatbot.

Autor: Takeshige-Amano H; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan., Oyama G; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan. g_oyama@juntendo.ac.jp., Ogawa M; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan., Fusegi K; Department of Neurology, Faculty of Medicine, Juntendo University Koshigaya Hospital, Saitama, Japan., Kambe T; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan., Shiina K; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan., Ueno SI; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan., Okuzumi A; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan., Hatano T; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan., Motoi Y; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan., Kawakami I; Department of Psychiatry, Faculty of Medicine, Juntendo University, Tokyo, Japan., Ando M; Department of Neurology, Faculty of Medicine, Juntendo University Koshigaya Hospital, Saitama, Japan., Nakayama S; Department of Neurology, Faculty of Medicine, Juntendo University Koshigaya Hospital, Saitama, Japan., Ishida Y; Department of Neurology, Takeda Sogo Hospital, Fukushima, Japan., Maei S; IBM Consulting, IBM Japan, Ltd., Tokyo, Japan., Lu X; IBM Consulting, IBM Japan, Ltd., Tokyo, Japan., Kobayashi T; IBM Consulting, IBM Japan, Ltd., Tokyo, Japan., Wooden R; IBM Consulting, IBM Japan, Ltd., Tokyo, Japan., Ota S; IBM Consulting, IBM Japan, Ltd., Tokyo, Japan., Morito K; GLORY Ltd., Tokyo, Japan., Ito Y; GLORY Ltd., Tokyo, Japan., Nakajima Y; GLORY Ltd., Tokyo, Japan., Yoritaka A; Department of Neurology, Faculty of Medicine, Juntendo University Koshigaya Hospital, Saitama, Japan., Kato T; Department of Psychiatry, Faculty of Medicine, Juntendo University, Tokyo, Japan., Hattori N; Department of Neurology, Faculty of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan. nhattori@juntendo.ac.jp.; Neurodegenerative Disorders Collaborative Laboratory, RIKEN Center for Brain Science, Saitama, Japan. nhattori@juntendo.ac.jp.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 Nov 01; Vol. 14 (1), pp. 26309. Date of Electronic Publication: 2024 Nov 01.
DOI: 10.1038/s41598-024-77220-0
Abstrakt: In super-aged societies, dementia has become a critical issue, underscoring the urgent need for tools to assess cognitive status effectively in various sectors, including financial and business settings. Facial and speech features have been tried as cost-effective biomarkers of dementia including Alzheimer's disease (AD). We aimed to establish an easy, automatic, and extensive screening tool for AD using a chatbot and artificial intelligence. Smile images and visual and auditory data of natural conversations with a chatbot from 99 healthy controls (HCs) and 93 individuals with AD or mild cognitive impairment due to AD (PwA) were analyzed using machine learning. A subset of 8 facial and 21 sound features successfully distinguished PwA from HCs, with a high area under the receiver operating characteristic curve of 0.94 ± 0.05. Another subset of 8 facial and 20 sound features predicted the cognitive test scores, with a mean absolute error as low as 5.78 ± 0.08. These results were superior to those obtained from face or auditory data alone or from conventional image depiction tasks. Thus, by combining spontaneous sound and facial data obtained through conversations with a chatbot, the proposed model can be put to practical use in real-life scenarios.
(© 2024. The Author(s).)
Databáze: MEDLINE
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