US 2018/0322954 A1Published application

Method and device for constructing medical knowledge graph and assistant diagnosis method

AssigneeHefei University of Technology

InventorsShuai DING, Shanlin YANG, Xiao SUN, Shikang HU, Hao WANG

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Abstract

The present invention discloses a method and a device for constructing a medical knowledge graph and an assistant diagnosis method. The assistant diagnosis method based on a medical knowledge graph comprises the steps of: acquiring complaint data and examination data of a patient and processing the data to obtain symptom entities and sign entities of the patient; searching, from the medical knowledge graph, disease entities associated with the symptom entities and the sign entities, calculating a posterior probability of each disease entity separately under a set of its corresponding symptom entities and sign entities; and outputting a disease entity with a maximum posterior probability as well as data corresponding to its associated nodes. The present invention provides an intelligent assistant diagnosis for clinical medicine to reduce the work burden of medical staff, relieve the medical pressure and reduce medical accidents.

Claims10

Dependent claims

A method and device for establishing medical knowledge graph, comprising the steps of:

collecting data from a medical database to construct a user dictionary;
processing electronic medical record data according to the user dictionary and a stop words library;
carrying out named entity recognition by a Conditional Random Fields Model (CRF) machine learning method on the processed data;
establishing an association relationship among the recognized entities;
and
establishing a medical knowledge graph based on the entities and the association relationship thereof;
using relevant medical language processing techniques to process the data of the electronic medical records, or perform text segmentation on the data of the electronic medical records, and remove stop word processing;
obtaining disease entities from processed diagnosis data, obtaining sign entities from processed health examination data, obtaining symptom entities according to processed complaint data of a patient, obtaining treatment entities according to treatment suggestion data, and obtaining department entities according to department information;
associating the disease entities with the symptom entities, the sign entities, the treatment entities and the department entities respectively, wherein the strength of the association relationship is expressed by:
Z=x/y
where y represents the number of medical records of a certain disease, x represents the total number of occurrences of a target entity in the medical records of a certain disease, and the target entity is any one of the symptom entity, the sign entity, the treatment entity and the department entity.

8 more elements

Dependencies are inferred from the claim text.

Facts

Application: 15/972,121Filed 5 May 2018
Priority: CN 201710317878.18 May 2017
Published: 8 Nov 2018
Term ends: Not estimatedThe source records don’t support an estimate.

Classification7 codes

G16H 50/20
ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or…: for…
G16H 10/60
ICT specially adapted for the handling or processing of patient-related medical or healthcare data: for patient-specific data, e.g. for electronic…
G16H 50/70
ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or…: for…
G16H 70/60
ICT specially adapted for the handling or processing of medical references: relating to pathologies

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