Deeper insight into speech characteristics of patients at ultra-high risk using classification and explainability models.

ABSTRACT:

Introduction

Peculiar use of language and even language deficits are one of the well-known signs of schizophrenia. Different language features analyzed using natural language processing and machine learning have been reported to differentiate patients at ultra-high risk for psychosis. However, it has not always been explained how, and to what extent, those linguistic markers allow the distinction of patients. This study aims to find relevant linguistic markers for classifying patients at ultra-high risk and explain how the detected markers contribute to the classification.

Methods

The first consultations with a psychiatrist of 68 patients (15 not-at-risk patients, 45 at-risk patients, and 8 patients with first episode psychosis) were recorded, transcribed verbatim, and annot

SUBMITTER: Kim-Dufor DH 

PROVIDER: S-EPMC12206705 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature