Preliminary exploration of the application of the DeepSeek-V3-0324 large-scale model in medication education in pharmaceutical outpatient clinics
- VernacularTitle:DeepSeek-V3-0324大模型在药学门诊用药教育中的应用初探
- Author:
Fengdan QIAN
1
;
Tingting JIA
1
;
Die ZHANG
1
;
Lichao ZHANG
1
;
Ya XUE
1
Author Information
1. Dept. of Pharmacy，Shanghai Municipal Hospital of Traditional Chinese Medicine Affiliated to Shanghai University of Traditional Chinese Medicine，Shanghai 200071，China
- Publication Type:Journal Article
- Keywords:
artificial intelligence;
pharmaceutical services;
pharmaceutical clinics;
rational drug use;
DeepSeek
- From:
China Pharmacy
2025;36(17):2192-2196
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE To explore a new model of intelligent medication education for pharmaceutical outpatient clinics by constructing dynamic HTML web pages through the DeepSeek-V3-0324 large-scale model. METHODS Clinical pharmacists integrated key clinical information such as patients’ basic information， medication history and medication precautions in real time， and generated a standardized medication education list through the DeepSeek-V3-0324 large-scale model and manual review. RESULTS The DeepSeek-V3-0324 large-scale model was applied in the pharmaceutical outpatient clinics to generate a personalized medication education list， which could effectively solve the disunity of pharmacy guidance caused by the lack of standardization of medication education and the difference of individualized experience of pharmacists in the traditional pharmaceutical outpatient clinics in the face of complex cases， and medication errors caused by forgetting or misremembering information among certain special patient populations after receiving medication education. CONCLUSIONS The transformation and application of artificial intelligence technology in pharmaceutical outpatient clinics is an innovation of pharmaceutical outpatient service means， which can provide patients with immediate and personalized medication education and improve the quality of pharmaceutical care. However， it is also necessary to face the lag of database update and the lack of risk management， as well as the lack of diversification of medication education lists.
