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@#Lung adenocarcinoma is a prevalent histological subtype of non-small cell lung cancer with different morphologic and molecular features that are critical for prognosis and treatment planning. In recent years, with the development of artificial intelligence technology, its application in the study of pathological subtypes and gene expression of lung adenocarcinoma has gained widespread attention. This paper reviews the research progress of machine learning and deep learning in pathological subtypes classification and gene expression analysis of lung adenocarcinoma, and some problems and challenges at the present stage are summarized and the future directions of artificial intelligence in lung adenocarcinoma research are foreseen.
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Objective To construct a COVID-19 CT image classification model based on lightweight RG DenseNet.Methods A RG-DenseNet model was constructed by adding channel and spatial attention modules to DenseNet121 for minimizing the interference of irrelevant features,and replacing Bottleneck module in DenseNet with pre-activated RG beneck2 module for reducing model parameters while maintaining accuracy as much as possible.The model performance was verified with 3-category classification experiments on the COVIDx CT-2A dataset.Results RG-DenseNet had an accuracy,precision,recall rate,specificity,and F1-score of 98.93%,98.70%,98.97%,99.48%,and 98.83%,respectively.Conclusion Compared with the original model DenseNet121,RG-DenseNet reduces the number of parameters and the computational complexity by 92.7%,while maintaining an accuracy reduction of only 0.01%,demonstrating a significant lightweight effect and high practical application value.
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OBJECTIVE:To optimize the extraction technology of Duoxuekang. METHODS:Using comprehensive score of salidroside,gallic acid content and extraction yield as indexes,U6(63)uniform design was designed to optimize the liquid-solid ra-tio,ethanol volume fraction and extraction time of Duoxuekang,then optimize extraction times,and verification test was conduct-ed. RESULTS:The optimal extraction technology was as follows as 50% ethanol,liquid-solid ratio of 1:14,soaking time of 1.5 h,reflux extraction for 1 h and repeated twice;the average extraction yield in 3 tests was 50.18%,contents of salidroside and gal-lic acid were 1.82 mg/g,16.54 mg/g (RSD≤0.84%,n=3). CONCLUSIONS:The optimized extraction technology for Duox-uekang is reasonable,simple and feasible.
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Chinese medicine and Tibetan medicine both belong to the traditional medicine, and have their unique background and theoretical systems. There are similar features and differences in diagnosis of disease, syndrome and treatment between Chinese medicine and Tibetan medicine. Tibetan Zhenbu disease is common and frequently-occurring in plateau area with high morbidity, which is corresponding to rheumatoid arthritis in modern medicine and the category of Bi syndrome in Chinese medicine. During a long period of clinical efficacy verification, Tibetan treatment of Zhenbu disease presents to be little side effects, good curative effect, safe and economic etc. In the review, according to the introduction of Tibetan medicine and Chinese medicine, Zhenbu disease of Tibetan medicine and Chinese Bi syndrome will be compared in their pathogeneses and treatments to understand advantages and peculiarities of Tibetan medicine. The development of Tibentan medicine in the future will also be pointed out.
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Objective:To discuss the dynamic three-dimensional reconstruction of tissue Doppler ultrasound cardiac image.Methods: To separate anatomical structure and function parameter information from Doppler ultrasound medical image, and then combines with the three-dimensional distribution to reconstruct it and fuse imaging.Results: Ultimately, it reveals the relationship between function parameter and anatomical structure. The dynamic three-dimensional reconstruction of tissue Doppler ultrasound cardiac image is also expounded in this paper.Conclusion: It scientifically completed the dynamic three-dimensional reconstruction of tissue Doppler ultrasound cardiac image by combining both tissue Doppler imaging and ultrasound medical image reconstruction technique. It is of great significance in clinical medicine.