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A Medical Guidance Model Driven by Subjective and Objective Knowledge
2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021 ; : 161-168, 2021.
Article in English | Scopus | ID: covidwho-1393646
ABSTRACT
Because of the impact of Corona Virus Disease 2019 (COVID-19), online medical services have developed rapidly and are widely accepted by people. People can find doctors for diagnosis and treatment by the name of the disease online. However, patients usually lack professional medical knowledge and have their own subjective preferences for health services, which makes it difficult for patients to accurately find a doctor that suits them. To this end, we proposed a medical guidance model driven by subjective and objective knowledge to provide decision support to patients. In the proposed model, the doctor's and disease's own information is regarded as objective knowledge, and the information of doctor feature extracted from patient reviews is regarded as subjective knowledge. They are fused into a knowledge graph. On this basis, a knowledge decision engine is designed to recommend the most suitable doctor based on the patient's objective conditions and subjective preferences. Finally, a prototype system is designed and developed to demonstrate the feasibility of the model as above. The system guides patients to improve their objective conditions and subjective preferences through inquiries, and returns recommended doctors to patients in an interpretable manner. The medical guidance model can effectively meet the personalized and professional needs of patients in online medical services, which has good practical value under the digital healthcare continues to become the trend of the future. © 2021 IEEE.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021 Year: 2021 Document Type: Article