ABSTRACT
This paper provides a comprehensive analysis of the current state of intelligent ophthalmology in China, including technological advancements, academic exchange platforms, policy support, future challenges, and potential solutions. Technologically, remarkable progress have been made in various areas of intelligent ophthalmology in China, including diabetic retinopathy, fundus image analysis, and crucial aspects such as quality assessment of medical artificial intelligence products, clinical research methods, technological evaluation, and industrial standards. Researchers are constantly improving the safety and standardization of intelligent ophthalmology technology by formulating clinical application guidelines and standards. Academic exchange platforms have been established to provide extensive collaboration opportunities for professionals across diverse fields, and various academic journals serve as publication platforms for intelligent ophthalmology research. Regarding public policy, the Chinese government has not only established a supportive policy environment for the advancement of intelligent ophthalmology through various documents and regulations, but provided a legal basis and management framework. However, there are still challenges to overcome, such as technological innovation, data privacy and security, outdated regulations, and talent shortages. To tackle these issues, there is a requirement for increased technological research and development, the establishment of regulatory frameworks, talent cultivation, and greater awareness and acceptance of new technologies among patients. By comprehensively addressing these challenges, intelligent ophthalmology in China is expected to continue leading the industry's global development, bringing more innovation and convenience to the field of ophthalmic healthcare.
ABSTRACT
To enhance the learning stickiness, improve low completion rate of online teaching, and promote teaching quality has become the key to solve the contradiction in online teaching. In this paper, taking the teaching of biochemistry as example, based on the trigger mechanism, maintenance mechanism and migration mechanism of sticky learning, guided by the three-dimensional goal of "knowledge and skills, process and method, emotional attitude and values", the BOPPPS (bridge-in, objective, pre-assessment, participatory-learning, post-assessment, summary) teaching model was combined with online teaching. According to the interactive behavior in the course learning space, the Spearman rank correlation analysis was performed by SPSS 18.0 software to comprehensively evaluate the learning stickiness degree. The research has found that, due to its "micro but refined, compact structure and student-centered" characteristics, BOPPPS combining with online teaching can effectively make up for the time and space limitations of offline teaching and the excessively broad online teaching, bring benefits from the perspectives of "inclusion, attraction and production", promote students' active learning, and practically improve learning stickiness. The research provides a new idea for creating online "golden" courses.
ABSTRACT
Objective To propose a multi-scale convolutional neural network ( CNN) based lesions detection method of fundus image,and evaluate its application in diabetic retinopathy ( DR) assisted diagnosis. Methods A multi-scale CNN based on lesions detection method of fundus image was proposed. Compared with the existing detection methods,the problem of poor robustness based on threshold segmentation and morphological segmentation was overcome. The idea of multi-scale grids detection without relying on manual pixel-by-pixel labeling was adopted in this algorithm,and the detection performance of small lesions was significantly improved. In addition, multiple DR lesions with high accuracy could be detected by the proposed loss function under the condition of weak labels and small data sets. Results At the level of lesions,the sensitivity and specificity of hard exudation lesions detection were 92. 17％ and 97. 17％,respectively. Compared with single-scale method,the sensitivity and accuracy of multi-scale method proposed in this paper increased by 7. 41％ and 5. 02％,respectively,and compared with other algorithm using the same public dataset IDRiD, the specificity of this algorithm increased by 55. 82％. This method could effectively detect the lesions in fundus images,and could give the basic range of the lesions. The average detection time of fundus images with a large number of lesions was 1. 59 seconds. Conclusions The DR lesions in the fundus image can be quickly and reliably identified,the location information of the lesions can be marked,and the influence of subjective factors can be reduced by using this algorithm, and it can be used to assist the clinician to conduct more effectively.
ABSTRACT
The "student-centered" concept highlights the dominant position of students in the teaching process and makes up for the deficiency of traditional teaching mode.Based on the above idea,the teaching team of the author's department tried to improve teaching effect through effective teaching design in biochemistry.Firstly,the teaching goal (the goal of knowledge,ability and emotion) and the important situational factors the learning situation analysis,the characteristics of the course and the class,etc)should be identified.suitable teaching strategies he inspiration strategy,exploration strategy and problem solution strategy,etc.),teaching method (discussion,case study,problem based learning,etc.) and proper assessment (such as the summative assessment with formative evaluation) should be determined to organize classroom teaching.At the end of the class the timely feedback and the teaching reflection should be carried outto extend classroom teaching to extra-curricular class.The results showed that effective teaching designismore likely to stimulate students' learning enthusiasm,promote students' deep learning and achieve better teaching effects.
ABSTRACT
Objective To explore the health effects of organic extracts from ambient air particulates with various diameters on the DNA damage of human peripheral blood lymphoctys. Methods Using a 5-stage air sampler, the ambient air particulats samples were collected in a residential area of Taiyuan city and were extracted with dichloromethane, acetone and methanol. The damage of DNA in human peripheral blood lymphocytes induced by organic extracts from ambient air particulates with various diameters at doses of 25, 50, 100 ,200 ?g/ml were detected by sigle cell gelelectrophoresis assay. Results The toxic efficiency of organic extraction of ambient air particulates increased with the decreases of the diameters of particulates. The tail lengthes of the comets induced by organic extracts from ambient air particulcctes with various diameters