Massive open online courses (MOOCs) , which has caused a large scale of medical edu-cation in recent years, has led to an exploration boom in medical education. By the end of November 2014, on four large domestic and foreign MOOCs platform, a total of 178 medical related MOOCs were found, accounting for 12.2% of the total number of courses, among which public health MOOCs accounted for 44.9%. In terms of medical education, MOOCs are not only a powerful supplement of existing medical ed-ucation and can assist dissemination of medical knowledge, they can also promote pedagogy innovation and improve teaching quality to a certain extent. Moreover, the huge amounts of data collected by MOOCs can also be used to develop research of students' learning behavior. In addition, by recruiting study objects, the researchers have begun to use MOOCs supporting scientific research. As a novel educational development, MOOCs face many challenges while they bring opportuni-ties for medical education. However, active prac-tice and exploration will bring more powerful vitality for its development in the medical field.

Objective To explore a new training method of nursing skills under 24 hours shift system in the practical training base in the college. Methods The practical training base in the college was rebuilt into a simulated hospital. 120 three-year-course nursing students in grade 2007 were divided into the control class and the experimental class with 60 students in each class. The control class adopted routine teaching method, including teacher demonstration, single project training, concentrated training before clinical practice. The experimental class participated in the tutoring mode of nursing skills under 24 hours shift system in simulated hospital. The cases were pre-designed and students acted as patients by tums. One teacher led 4 students into nursing skill training by day shift, evening shift and mid-night shift. The teaching effect was compared between two classes. Results There was significant difference between the two groups in comprehensive technique test and graduation theoretical test score. Clinical nursing teachers thought the skill training in simulated hospital under 24 hours shift system can help students prepare for the nursing work in hospital ahead of time and improve their comprehensive capability. Conclusions Training mode of nursing skills in simulated hospital under 24 hours shift system is feasible for enhancing nursing skills.

Objective To investigate the clinical significance of serum CEA , CA19-9, CA72-4, CA242, CA50, PGⅠand PGR ( PGⅠ/PGⅡ) in the Diagnosis of preoperative and postoperative gastric cancer.Methods Retrospective study.The levels of CEA , CA19-9, CA72-4, CA242, CA50, PGⅠand PGⅡin serum of 41 patients with gastric cancer preoperative and postoperative and 60 healthy people were detected by AutoLumo A2000 chemiluminescence immunoassay and compared.Statistical analysis was performed using Rank-sum test by SPSS 17.0.Results The median of CEA, CA19-9, CA72-4, CA242, CA50, PGI, PGII and PGR in postoperative gastric cancer group were 3.79 ng/ml, 17.85 U/ml, 3.50 U/ml, 14.52 U/ml, 17.62 U/ml, 32.81 ng/ml, 11.48 ng/ml, 3.35.The postoperative gastric cancer group were 1.67 ng/ml, 7.76 U ml, 1.73 U/ml, 6.30 U/ml, 7.57 U/ml, 20.56 ng/ml, 5.71 ng/ml, 2.94.The healthy group were 1.53 ng /ml, 7.59 U/ml, 1.47 U/ml, 6.08 U/ml, 5.68 U/ml, 90.86 ng/ml, 14.85 ng/ml, 6.67.There were statistical differences in the serum levels of CEA , CA19-9, CA72-4, CA242, CA50, PGⅠ, PGⅡand PGR among different groups (chi-squared values were 79.108, 20.678, 20.374, 7.252, 56.73, 131.212, 20.38, 86.37, P<0.05).By the Mann-Whitney rank sum test,the serum levels of CEA , CA19-9, CA72-4, CA242 and CA50 in patients with preoperative gastric cancer were significantly higher than those in healthy controls (Z values were -8.598, -4.425, -4.365, -2.000,-7.420, P<0.05).The level of postoperative group was significantly lower than that of preoperative group (Z value were -4.641, -2.383, -2.459, -2.399, -2.903, P<0.05).The serum PGⅠ, PGⅡand PGR levels in patients with preoperative gastric cancer were significantly lower than those in healthy controls (Z values were -10.309, -2.695, 8.637, P<0.05).The PGⅠlevel in the postoperative group was significantly lower than that in the preoperative group (Z value was -2.109, P<0.05).PGⅡ,PGR levels of postoperative group were lower than those of preoperative group , but the difference were not statistically significant.(Z values were -1.506,-0.838, P values were 0.132,0.402).Conclusion The detection of the seven serum markers can help to preoperative diagnosis and postoperative monitoring of gastric cancer .

Artificial intelligence (AI) is an emerging science and technology that studies and develops theories, methods, technologies, and application systems for simulating and expanding human intelligence. AI has made great breakthroughs in the field of intelligent medicine, and has shown great potential in the diagnosis and treatment of diabetic retinopathy (DR), retinopathy of prematurity, and other fundus diseases. A number of clinical trials on the application of AI technologies to DR screening have been carried out in the domestic and overseas, which not only have a high accuracy rate, but also save doctors' reading time and reduce the burden of society, medical work and patients. However, due to the lack of evaluation system for DR intelligent diagnosis technology, the accuracy of AI system still lacks of big data verification. Secondly, most of the color fundus photographs are taken in the posterior 45°, which only show the most vulnerable areas, making some lesions undetectable. In addition, the current DR screening system has not yet been applied to the clinic, most of which are in the stage of prospective research and trials. There are still many obstacles from the environment to the hospital or the clinic. Doctors cannot use real patient data to evaluate the AI system, so it is not popular in clinical practice. In the future, DR screening algorithms and diagnostic models can be further improved and established to make DR AI screening more accurate.

Objective:To analyze the reform actions on raising the appropriateness of inpatient care use, as well as the current situation, so as to provide suggestions on improving the appropriateness.Methods:Policies and literatures on the appropriateness of inpatient care use released from 2009 to 2021 were collected from such official websites as the State Council and China National Health Commission as well as literature databases from home and abroad, for a text analysis. Based on the data of China Health Statistics Yearbook(2010-2021) and The Sixth National Health Service Survey Report (2018), descriptive methods were adopted to analyze the situation of inpatient care use in China. Results:Since the new healthcare reform, the Chinese government had standardized the hospitalization standards and procedures to minimize inappropriate use of inpatient care, increased financial subsidies for public hospitals to minimize their inappropriate patient attraction merely for economic interests, and reformed the medical insurance payment methods so as to regulate physicians′ behavior. Under the influence of the above policies, the average length of stay decreased from 10.5 days in 2009 to 9.1 days in 2019, with an average annual growth rate of -1.42%. The average waiting time in hospitals decreased from 3.6 days in 2008 to 1.5 days in 2018.From 2012 to 2019, the admission rate increased from 13.2% to 19.0%.Conclusions:Since the new healthcare reform, the average length of stay in China has decreased year by year, but the admission rate has increased year by year. Therefore, it is necessary to further reduce the inappropriate utilization of inpatient care use by speeding up the construction of the close-type medical alliances, improving the reform of payment methods, refining the performance appraisal standards for medical staff and strengthening supervision mechanism.

Since the outbreak of the Coronavirus Disease 2019 (COVID-19), universities have carried out online education for public health and preventive medicine courses under the policy of "Suspending Classes Without Stopping Learning" launched by the Chinese government. The Public Health and Preventive Medicine Committee of the Ministry of Education Steering Committee for Medical Education investigated the online teaching activities in the member universities. This study presents the survey results, discusses the existing problems, and proposes suggestions for further reforms on mixed teaching activities.

Since the outbreak of the Coronavirus Disease 2019 (COVID-19), universities have carried out online education for public health and preventive medicine courses under the policy of "Suspending Classes Without Stopping Learning" launched by the Chinese government. The Public Health and Preventive Medicine Committee of the Ministry of Education Steering Committee for Medical Education investigated the online teaching activities in the member universities. This study presents the survey results, discusses the existing problems, and proposes suggestions for further reforms on mixed teaching activities.

Objective:To analyze the lifestyle for brain health related factors and demographic characteristics through machine learning to achieve the assessing effect of mild cognitive impairement prevalence risk among rural elderly people in Guizhou.Methods:From July to August 2019, a multi-stage cluster random sampling method was used to select 1 235 rural elderly people aged 60 years and above in Guizhou Province as the subjects, and the investigation was performed with questionnaire and physical examination.The Mini-Mental State Examination (MMSE) was used to assess cognitive function, and the important features and optimal number of features based on 12 LIBRA factors and 4 demographic characteristics were selected.Logistic regression and random forest algorithm were used to establish a evaluation model for the risk of mild cognitive impairment in the elderly.The evaluation efficacy of the model was also assessed using a combination of precision, accuracy, sensitivity, specificity, F1 score and area under curve (AUC) of receiver operating characteristic curve, and the Delong method was used to check the difference of AUC values between the two models.Results:A total of 291 subjects were diagnosed with mild cognitive impairment, with a detection rate of 23.56% (291/1 235). The AUC values of logistic regression and random forest models evaluating the risk of mild cognitive impairment in the rural elderly were 0.758 and 0.820, respectively, and the differences were statistically significant(both P<0.05). The random forest model had better evaluations with an accuracy of 0.823, precision of 0.805, sensitivity of 0.874, specificity of 0.767 and F1 score of 0.838, all of which were better than those of the logistic regression model.And the random forest model was also more stable after 10-fold cross-validation. Conclusion:The lifestyle for brain health related factors combined with demographic characteristics can more accurately evaluate the risk of mild cognitive impairment among rural elderly people in Guizhou.The random forest model is better than the logistic regression model.

Purpose/Significance To deeply analyze the research progress on the application of medical knowledge graph in the field of stroke,to discuss the problems of the development of stroke knowledge graph in China,and to put forward suggestions for the construc-tion of stroke knowledge graph.Method/Process By reviewing and analyzing the relevant literature,the application of medical knowledge graph in the field of stroke is sorted out and summarized.Result/Conclusion There are still many deficiencies in the development of stroke knowledge graph in China,and in the future,in-depth research can be carried out from four aspects,namely,expanding the ap-plication scope of knowledge graph,promoting the fusion of knowledge graph,developing more efficient algorithms,and upgrading to cog-nitive graph by joint artificial intelligence(AI).

Objective:To systematically review the risk factors of postoperative delirium in patients with liver surgery, in order to provide reference for early clinical prevention of postoperative delirium in patients with liver surgery.Methods:PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI) , Wanfang Database, VIP and China Biomedical Literature Database were searched by computer from the establishment of the database to July 31, 2021. Two researchers conducted literature screening, quality evaluation and data extraction. RevMan 5.4 was used for data analysis.Results:Finally, 15 articles were included. Meta-analysis results showed that advanced age ( OR=1.13, 95% CI: 1.06-1.22, Z=3.49, P=0.0005) , history of cerebrovascular disease ( OR=3.27, 95% CI: 1.89-5.66, Z=4.24, P<0.000 1) , history of hepatic encephalopathy ( OR=2.49, 95% CI: 1.70-3.65, Z=4.68, P<0.000 01) , history of mental illness ( OR=2.82, 95% CI: 1.52-5.22, Z=3.30, P=0.001) , history of sedative-hypnotic use ( OR=4.12, 95% CI: 1.99-8.52, Z=3.82, P=0.000 1) , history of drinking ( OR=1.96, 95% CI: 1.18-3.26, Z=2.61, P=0.009) , postoperative infection ( OR=5.76, 95% CI: 4.24-7.84, Z=11.18, P<0.000 01) were independent risk factors for postoperative delirium in patients with liver surgery. Increased preoperative albumin level ( OR=3.31, 95% CI: 0.19-0.52, Z=4.52, P<0.000 01) was a protective factor for postoperative delirium in patients undergoing liver surgery. There were no statistically significant differences in effects of end-stage liver disease model score, preoperative serum total bilirubin level, postoperative increased serum sodium level, postoperative ICU admission, acute physiology and chronic health scores on postoperative delirium in patients with liver surgery ( P>0.05) . Conclusions:Advanced age, history of cerebrovascular disease, history of mental illness, history of hepatic encephalopathy, history of sedative-hypnotic use, history of alcohol consumption and postoperative infection are independent risk factors for postoperative delirium in patients with liver surgery, and elevated preoperative albumin level is associated with postoperative delirium. protective factor.