Language patterns in Japanese patients with Alzheimer disease: A machine learning approach.

ABSTRACT:

Aim

The authors applied natural language processing and machine learning to explore the disease-related language patterns that warrant objective measures for assessing language ability in Japanese patients with Alzheimer disease (AD), while most previous studies have used large publicly available data sets in Euro-American languages.

Methods

The authors obtained 276 speech samples from 42 patients with AD and 52 healthy controls, aged 50 years or older. A natural language processing library for Python was used, spaCy, with an add-on library, GiNZA, which is a Japanese parser based on Universal Dependencies designed to facilitate multilingual parser development. The authors used eXtreme Gradient Boosting for our classification algorithm. Each unit of part-of-speech and depend

SUBMITTER: Momota Y 

PROVIDER: S-EPMC11488616 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature