Work

Potential and biases of large language model simulation for public surveys on Alzheimer's disease therapies

Year: 2026

Type: article

Source: Journal of Alzheimer s Disease

DOI: 10.1177/13872877261464182

Authors: Kenichiro Sato, Yoshiki Niimi, Ryoko Ihara, Kazushi Suzuki, Atsushi Iwata, Takeshi Iwatsubo

Institutions: University of Tokyo Hospital, The University of Tokyo, Tokyo Metropolitan Institute of Gerontology, National Defense Medical College

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: Japan Agency for Medical Research and Development, Japan Society for the Promotion of Science

Awards: 脳アミロイド血管症およびアミロイド関連画像異常（ARIA）のリスクファクターに関するレジストリ研究, 認知症プレクリニカル期・プロドローマル期を対象とするトライアルレディコホート構築研究, アルツハイマー病疾患修飾療法の待機時間短縮に向けたデータサイエンス戦略, 特性に基づく非アルツハイマー病の分類と超早期の臨床的特徴の検討, G7427483188, G8445478933, G8712897241

OpenAlex ID: W7166346039

FWCI:

Cites: 27

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