  During the growing popularity of electronic medical records, electronic
medical record (EMR) data has exploded increasingly. It is very meaningful to
retrieve high quality EMR in mass data. In this paper, an EMR value network
with retrieval function is constructed by taking stroke disease as the research
object. It mainly includes: 1) It establishes the electronic medical record
database and corresponding stroke knowledge graph. 2) The strategy of
similarity measurement is included three parts(patients' chief complaint,
pathology results and medical images). Patients' chief complaints are text
data, mainly describing patients' symptoms and expressed in words or phrases,
and patients' chief complaints are input in independent tick of various
symptoms. The data of the pathology results is a structured and digitized
expression, so the input method is the same as the patient's chief complaint;
Image similarity adopts content-based image retrieval(CBIR) technology. 3) The
analytic hierarchy process (AHP) is used to establish the weights of the three
types of data and then synthesize them into an indicator. The accuracy rate of
similarity in top 5 was more than 85\% based on EMR database with more 200
stroke records using leave-one-out method. It will be the good tool for
assistant diagnosis and doctor training, as good quality records are colleted
into the databases, like Doctor Watson, in the future.
