Intelligent auxiliary diagnosis system

Abstract

The invention provides an intelligent auxiliary diagnosis system, and the system comprises a cloud platform and a plurality of terminals which are connected with the cloud platform through a network.The cloud platform comprises a cloud platform algorithm module, and the cloud platform algorithm module trains an intelligent diagnosis auxiliary model based on a large number of disease pictures at an early stage through the artificial intelligence technology. Through clinical testing, the model is embedded into the cloud platform so as to implement the intelligent auxiliary diagnosis after the sensitivity and specificity reach an accurate diagnosis standard, and the system can automatically feeds back an intelligent diagnosis result matched with the disease pictures obtained by the terminals, and transmits the diagnosis result to the terminals as the reference of doctors. The system promotes the intelligentization and informationization of the related medical services. The system buildsa remote medical artificial intelligent service network, achieves the hierarchical medical services, and can guarantee the performances and safety. The system reduces the application and maintenance cost. The system facilitates the improvement of the initial diagnosis capability for diseases at the basic level, and enables the hierarchical diagnosis and treatment system to be complete.

Description

technical field [0001] The invention relates to the field of medical instruments, in particular to an intelligent auxiliary diagnosis system for diabetic retinopathy. Background technique [0002] Diabetic retinopathy (Diabetic Retinopathy, DR) is a common blinding eye disease. China is the country with the largest number of type 2 diabetes patients in the world, and the prevalence and blindness rate of DR are also increasing year by year. It is currently the number one blinding disease among working-age people. Currently, the prevalence of DR among people with diabetes in my country is 24.7%-37.5%. According to the statistics of the International Diabetes Federation, as of 2015, there were about 110 million people with diabetes in my country, and based on this, it is estimated that there are about 27 million people with DR in my country. With the substantial increase of diabetic patients, the number of DR patients will increase exponentially in the future, and the prevent...

AI Technical Summary

Problems solved by technology

Even if you master the fundus photography technology, you cannot analyze the fundus photography images independently. You need to go to an ophthalmology department with a certain scale to determine DR lesions and grades after collecting fundus images, which greatly affects the efficiency of DR screening and the experience of DR patients. , making grassroots DR screening difficult to carry out

Through preliminary market research, the project team found that some community hospitals at the grassroots level do not even have the corresponding fundus camera equipment for screening, which has a huge resource gap

Images