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Objective:To survey the application of an intelligent consultation system for common eye diseases and evaluate its applicational effectiveness on an internet hospital platform.Methods:A cross-sectional study was performed in Zhongshan Ophthalmic Centre of Sun Yat-sen University.Natural language processing technology was applied to develop the intelligent consultation system for common eye diseases.Its efficiency and quality were evaluated.The survey data were collected from February 1 to 29, 2020 to analyze the demographic information, consultation time, consultation category, consultation content, service satisfaction.This study protocal was approved by an Ethic Committee of Zhongshan Ophthalmic Centre of Sun Yat-sen University(2020KYPJ095).Results:The intelligent consultation system for common eye diseases was developed and successfully deployed in Internet Hospital of Zhongshan Ophthalmic Center.The repeatability and accuracy of the intelligent consultation system were 100.0% and 99.8%, respectively.During February 1 to 29, 2020, the intelligent consultation system served 6 462 patients, including 3 082 males(47.7%) and 3 380 females(52.3%). The average age of patients was 32.3 years old.Total of 1 135(17.6%) patients used the intelligent guidance consultation, and 5 375(82.4%) patients used the intelligent outpatient consultation.The intelligence consultation system was applied by 223 patients per day with a maximum of 74 patients per hour.The survey showed that 25.6% and 36.4% of the patients felt very satisfied and relatively satisfied with the efficiency of the intelligent consultation service, respectively; 24.3% and 37.8% of the patients were very satisfied and relatively satisfied with the quality of the intelligent consultation service, respectively.Conclusions:Intelligent consultation system for common eye diseases can meet the needs of patients because of its high repeatability and accuracy.Patients are satisfied with the service efficiency and quality of the intelligent consultation system, which avoids the risk of cross infection and releases the burden of medical staff.
RESUMO
With the global trend of aging populations,the prevalence of blindness is expected to increase.However,due to deficiencies and imbalances,medical resources are far from satisfactory for ophthalmic disease diagnosis and management,particularly in primary medical facilities of developing countries.Eyeball is a visualized organ with its superficial position and transparent refractory media.Therefore,many ophthalmic diseases can be screened and diagnosed from images and photographs,such as cataract,cornea diseases and retinopathy,etc.As the development of data mining technology and accumulation of large amount of ophthalmic clinical data,the conditions are ripe for establishment of artificial intelligence (AI) diagnostic platform.Currently,attention should be focused on integrating the abundant ocular imaging resources,practically applying the data mining technology and gradually developing the universal AI platform for the management of ophthalmic disease.
RESUMO
Transplantations for repairing tissue and organ defects caused by disease and injury require a large number of donor tissues and organs.Therefore,people are increasingly hoping to restore or rebuild normal physical functions by establishing the body's own regenerative capacity.For this reason,regenerative medicine is rapidly emerging and becoming a research hotspot.The regeneration of tissues and organs is a complex process involving multiple layers of structures and requiring multiple factors to interact.Compared with traditional biomolecular technologies,biological omics based on biomolecular groups has obvious advantages in regenerative medicine researches and has became an important tool correlational researches.In this paper,the methods and progress of biomedical techniques for regenerative medicine researches in recent years were summarized,and the advantages of biological omics technology in regenerative medicine were analyzed and prospected.