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As an important industry in China, rose has extremely important economic value and ornamental value. However, affected by human factors and planting environment, even roses of the same variety will have different levels of classification. In order to solve the low efficiency of wrong classification and missing classification caused by manual visual classification and realize the transformation of rose classification from manual judgment to machine independent recognition, this paper first performs data enhancement, image naming and other operations on 200 manually photographed yellow rose images of 5 levels of the same variety, and constructs an image database. Then, in Python language and tensorflow2.0 deep learning tool, design rose classification algorithm based on artificial neural network(ANN), rose classification algorithm based on convolution neural network(CNN) and rose classification algorithm based on feature extraction(FE) and artificial neural network(ANN). Finally, the experimental results show that the third algorithm significantly speeds up the running speed and significantly improves the average recognition rate compared with the first two algorithms, which effectively solves the problems of wrong or missing classification and low classification efficiency in manual intuitive classification, and realizes the transformation from manual classification to machine independent classification.

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To update the efficacy and safety of short-term (#3 months) dual antiplatelet therapy (DAPT) and standard (6-12 months) DAPT in patients undergoing percutaneous coronary intervention. In addition, we also explored the duration of DAPT in patients at high bleeding risk (HBR). In PubMed, Embase, and Cochrane Library, we electronically searched among all the studies from the establishment of the database to December 8, 2021, for randomized controlled trials (RCTs). Nine randomized controlled trials (45,661 patients) ultimately met the inclusion criteria. The pooled analysis revealed that, compared with standard DAPT, #3month DAPT significantly reduced major adverse cardiovascular event {hazard ratio (HR) = 0.89, 95% confidence interval (CI) [0.82-0.97]}, all-cause mortality [HR = 0.88, 95% CI (0.78-0.99)], cardiovascular mortality [HR = 0.79, 95% CI (0.65-0.97)], major bleeding [HR = 0.72, 95% CI (0.56-0.93)], and any bleeding [HR = 0.57, 95% CI (0.50-0.66)], while no significant differences in the risk of myocardial infarction, stent thrombosis, and stroke. In patients with HBR, the results showed that #3-month DAPT significantly reduced major bleeding [HR = 0.35, 95% CI (0.14-0.88)] and any bleeding [HR = 0.53, 95% CI (0.41-0.67)] compared with standard DAPT, while the risk of other outcomes was not statistically different. In conclusion, this study showed that #3-month DAPT may be a valid option for most patients after percutaneous coronary intervention. Because reductions in major adverse cardiovascular event, all-cause mortality, and cardiovascular mortality were not seen in patients with HBR, this also highlights the need for specific studies in these patients about optimal duration of antiplatelet therapy.