ABSTRACT
The establishment of mental health assessment system provides a new way for the early diagnosis of mental health problems, in view of the growing population of mental diseases and problems and the uneven distribution of mental health resources. In the mental health assessment system, intelligent assistant diagnosis can assist or help psychiatrists improve their work efficiency. Intelligent assistant diagnosis provides technical support for predictive screening and auxiliary diagnosis of mental health problems. It is an intelligent diagnosis research based on big data analysis and machine learning in mental health assessment system. This article mainly reviews the application methods, the application progress in the field of mental health, as well as related technical issues and safety issues, and prospects the future research development.
ABSTRACT
With the booming development of medical information technology and computer science, the medical services industry is gradually transiting from information technology to intelligence. The medical knowledge graph plays an important role in intelligent medical applications such as knowledge questions and answers and intelligent diagnosis, and is a key technology for promoting wise medical care and the basis for intelligent management of medical information. In order to fully exploit the great potential of knowledge graphs in the medical field, this paper focuses on five aspects: inter-drug relationship discovery, assisted diagnosis, personalized recommendation, decision support and intelligent prediction. The latest research progress on medical knowledge graphs is introduced, and relevant suggestions are made in light of the current challenges and problems faced by medical knowledge graphs to provide reference for promoting the wide application of medical knowledge graphs.
Subject(s)
Pattern Recognition, Automated , Medical InformaticsABSTRACT
OBJECTIVE@#To analyze the role of artificial intelligence technology in the diagnosis and treatment of the COVID-19.@*METHODS@#To study the application progress and characteristics of artificial intelligence technology in CT image diagnosis, routine outpatient data diagnosis and complication prediction of COVID-19, and analyze the performance of the algorithm and the clinical benefits obtained in the process of diagnosis and treatment.@*RESULTS@#The performance of artificial intelligence technology in assisted diagnosis of the diagnosis and prediction of complications is relatively satisfactory.@*CONCLUSIONS@#Artificial intelligence technology can help medical institutions effectively alleviate the shortage of medical resources, improve diagnosis efficiency and treatment quality in the COVID-19 epidemic. Related models have good clinical application value.
Subject(s)
Humans , Algorithms , Artificial Intelligence , COVID-19 , SARS-CoV-2 , TechnologyABSTRACT
Objective To discuss the use of knowledge graph technology to connect various trivial and fragmented knowledge in various medical information systems and support comprehensive knowledge retrieval and intelligent medical applications such as Q & A and clinical decision support.Methods Based on the construction of medical field ontology and semantic labeling of medical knowledge base,the medical knowledge graph was constructed and applied to intelligent medicine,with chronic disease taken as an example.Results The construction method of medical knowledge graph and its application in semantic analysis,reasoning and disease-assisted diagnosis system based on medical knowledge base were put forward.Conclusion The application of intelligent medicine based on knowledge graph will play an important role in contradiction between the supply of high-quality medical resources and increasing medical requirements.