Construction of hypertension structured database based on Yi-9B big language model
10.3969/j.issn.1671-8348.2025.01.011
- VernacularTitle:基于Yi-9B大语言模型的高血压结构化数据库的构建
- Author:
Zhouqi ZHANG
1
;
Yong LIU
;
Bitian FAN
;
Xintong WEI
;
Weijun YI
Author Information
1. 中国人民解放军陆军军医大学第二附属医院疼痛与康复科,重庆 400037
- Keywords:
artificial intelligence;
large language model;
high blood pressure;
structured database;
diag-nosis and treatment efficiency
- From:
Chongqing Medicine
2025;54(1):57-62
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a hypertension structured database based on Yi-9B large language model by aiming at the large amount of unstructured data generated in the process of hypertension diagnosis and treatment in order to elevate the efficiency of data management and provide the support for clinical deci-sion-making.Methods The key clinical informations of 114 369 patients with hypertension visiting in the Sec-ond Affiliated Hospital of Army Medical University during 2014-2023 were extracted.The Yi-9B large lan-guage model was used for conducting the entity identification and data structuring,and the database architec-ture was designed for statistical analysis and clinical application.Results After the database structuring process,the mean values of systolic and diastolic blood pressure were(149.98±20.55)mmHg and(86.90±13.75)mmHg,respectively.According to the classification of blood pressure level,the proportions of the nor-mal high value for high risk,very high risk of hypertension grade 1,and very high risk of hypertension grade 2 were the highest,which accounted for 20.73％,27.80％and 19.59％respectively.52.64％of the patients were complicated with heart disease,10.18％with complicating diabetes and 12.71％with complicating hy-perlipidemia.Logistic regression analysis showed that＞50-60 and＞60-70 years old was the high incidence age segment,moreover the systolic blood pressure showed an increasing trend with the age increase,reflecting the universality of hypertension in aging.This database significantly improved the efficiency of diagnosis and treatment in clinical application and realized the efficient analysis and management of data.Conclusion The hyper-tension structured database based on Yi-9B large language model effectively processes the unstructured data,significantly improves the efficiency of data extraction and management,helps to optimize the diagnosis and treatment decision-making,improves the management efficiency and provides the support for intelligent man-agement and personalized diagnosis and treatment.
