Headache-assisted Decision-making System Based on Knowledge Graph

Knowledge graph is essentially a large-scale semantic network that describes real-world concepts, entities, events and the relationships between them in a more comprehensible way. It has the advantages of massive scale, semantic richness, friendly structure and fine quality. Its advantages are in line with the development of information technology, and it is widely used in systems such as intelligent recommendation, assisted decision-making and automatic question and answer, and is also a focus of research in the field of Internet + Medicine. According to epidemiological statistics, the prevalence of primary headache in China is 23.8%, including 10.8% for tension-type headache and 9.3% for migraine. Headache is easy to develop in all age groups and has many causes, which seriously affects people's daily work and life. In order to help headache patients improve their medical experience, record the characteristics of headache attacks in a more professional way, and assist doctors in clinical decision-making, this paper constructs a headache diagnosis knowledge graph by integrating clinical guidelines and knowledge data in the field of headache. In line with the medical needs of headache patients and clinicians, four functional modules have been designed: pre-diagnosis, headache diary, headache information, and assisted decision-making. Ultimately, the headache-assisted decision-making system based on knowledge graph has been successfully implemented, providing doctors and patients with a medical platform with good social value in the field of headache specialties.