26 AUTOMATED ASSESSMENT OF LANGUAGE FUNCTION IN PATIENTS WITH SCHIZOPHRENIA USING NATURAL LANGUAGE PROCESSING TECHNOLOGY
Authors: Lv Lin 
Published: February 2025

Abstract

Background
Schizophrenia patients generally have language dysfunction, such as unclear logical expression, difficulty in language communication, and incoherent vocabulary expression. And natural language processing technology can analyze and understand text data, which has important guiding significance in the study of schizophrenia. With the development of artificial intelligence technology, research has found that by analyzing the speech abilities of patients with schizophrenia, natural language processing techniques can uncover abnormal features of their language patterns, such as frequency of vocabulary use, complexity of grammatical structures, semantic coherence, and other deviations. With the help of this technology, it is possible to evaluate and treat the language function of patients with schizophrenia in more detail, and assist doctors in determining the progression of the patient’s condition and changes in their psychological state. Therefore, the study uses a natural language processing assessment system to analyze the language function of patients with schizophrenia, in order to provide technical support for the treatment of schizophrenia patients.

Methods
The experimental group consists of 40 patients with schizophrenia, aged between 18 and 55 years old. The control group consisted of 40 healthy volunteers who were similar in age and gender to the experimental group. The control group selected 40 healthy volunteers who were similar in age and gender to the experimental group. During the experiment, the language function of two groups of patients was first evaluated, including six aspects such as vocabulary diversity, grammatical correctness, semantic coherence, topic relevance, accuracy of emotional expression, and language fluency. Both the experimental group and the control group patients engaged in a 15-minute free conversation in their natural state, with the conversation content recorded and converted into text for evaluation by the natural language system. And according to the evaluation results, corresponding intervention treatments were taken for the experimental group, while no treatment was given to the control group.

Results
From the data in Table 1, it can be seen that after a one-month observation period, the experimental group showed certain improvements in vocabulary diversity, grammatical correctness, semantic coherence, topic relevance, emotional expression accuracy, and language fluency, while the control group showed no significant changes in these indicators before and after.

Discussion
The results of this study indicate that the automated language function assessment system for schizophrenia patients, combined with natural language processing technology, can effectively monitor changes in patients’ language function. Especially two months after treatment, it can be seen that the experimental group patients have significantly improved in vocabulary diversity and semantic coherence. This further indicates that the technology can provide support for the treatment of patients with schizophrenia.

Funding
No. JJKH20240221YY.