ABSTRACT
In recent years, the prevalence of cardiovascular disease (CVD) in China has been increasing year by year, and it has become a major public health concern. The prevention and control of chronic CVD is inseparable from effective early screening. However, due to the imbalance in the level of economic and social development in various parts of China, the universality and accessibility of screening in some areas still need to be improved. The fundus retinal blood vessel is the only vessel in the whole body that can be directly observed. Studies have found that its morphological and functional changes are related to the occurrence and development of many CVD, and it has the potential to become a tool for assessment and prediction. This review intends to introduce the research progress of retinal blood vessels in the evaluation and prediction of cardiovascular disease in recent years.
ABSTRACT
A key challenge for estimating the epidemiological parameters of the COVID-19 out-break in Wuhan is the discrepancy between the officially reported number of infections and the true number of infections. A common approach to tackling the challenge is to use the number of infections exported from Wuhan to infer the true number in the city. This approach can only provide a static estimate of the epidemiological parameters before Wuhan lockdown on January 23, 2020, because there are almost no exported cases thereafter. Here, we propose a method to dynamically estimate the epidemiological parameters of the COVID-19 outbreak in Wuhan by recovering true numbers of infections from day-to-day official numbers. Using the method, we provide a comprehensive retrospection on how the disease had progressed in Wuhan from January 19 to March 5, 2020. Particularly, we estimate that the outbreak sizes by January 23 and March 5 were 11,239 [95% CI 4,794-22,372] and 124,506 [95% CI 69,526-265,113], respectively. The effective reproduction number attained its maximum on January 24 (3.42 [95% CI 3.34-3.50]) and became less than 1 from February 7 (0.76 [95% CI 0.65-0.92]). We also estimate the effects of two major government interventions on the spread of COVID-19 in Wuhan. In particular, transportation suspension and large scale hospitalization respectively prevented 33,719 and 90,072 people from getting infected in the nine-day time period right after its implementation.
ABSTRACT
For the past few years,artificial intelligence (AI) technology has developed rapidly and has become frontier and hot topics in medical research.While the deep learning algorithm based on artificial neural networks is one of the most representative tool in this field.The advancement of ophthalmology is inseparable from a variety of imaging methods,and the pronounced convenience and high efficiency endow AI technology with promising applications in screening,diagnosis and follow-up of ophthalmic diseases.At present,related research on ophthalmologic AI technology has been carried out in terms of multiple diseases and multimodality.Many valuable results have been reported aiming at several common diseases of ophthalmology.It should be emphasized that ophthalmic AI products are still faced with some problems towards practical application.The regulatory mechanism and evaluation criteria have not yet integrated as a standardized system.There are still a number of aspects to be optimized before large-scale distribution in clinical utility.Briefly,the innovation of ophthalmologic AI technology is attributed to multidisciplinary cooperation,which is of great significance to China's public health undertakings,and will be bound to benefit patients in future clinical practice.
