PATENT CLAIM ANALYSIS

Application Number: 15972121
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-11
Patent Classification: ["705", "002000"]

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.

Claim (Index 1):
A method and device for establishing medical knowledge graph, comprising the steps of:\n 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:\n Z=x/y  \n 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.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 93.0
- Lexical Diversity: 2.20588
- Patent Class: 705.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15804033', '15609800', '11932190', '09522792', '11258507']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1105949410548897
- 35 USC 102 Novelty (BERT): 0.4910849318579861
- Combined Prediction Score: 0.1486439401351993
- Mean Citation Score: 187.202062
- Max Citation Score: 224.83003
- Similarity Product: 154.79371724065902

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test