Construction of an Assisted Model Based on Natural Language Processing for Automatic Early Diagnosis of Autoimmune Encephalitis.

ABSTRACT:

Introduction

Early diagnosis and etiological treatment can effectively improve the prognosis of patients with autoimmune encephalitis (AE). However, anti-neuronal antibody tests which provide the definitive diagnosis require time and are not always abnormal. By using natural language processing (NLP) technology, our study proposes an assisted diagnostic method for early clinical diagnosis of AE and compares its sensitivity with that of previously established criteria.

Methods

Our model is based on the text classification model trained by the history of present illness (HPI) in electronic medical records (EMRs) that present a definite pathological diagnosis of AE or infectious encephalitis (IE). The definitive diagnosis of IE was based on the results of traditional etiologica

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC9338198 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature