Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Apr 2020
Review[An analysis of global research on SARS-CoV-2].
The SARS-CoV-2 has been spread to 26 countries around the world since its outbreak. By February 16, 2020, more than 68 000 people had been diagnosed with COVID-19. Researchers from all over the world have carried out timely studies on this public health emergency and produced a number of scientific publications. ⋯ The literatures related to SARS-CoV-2 are emerging rapidly. It is necessary to sort out and summarize the research topic in time, which has a good reference value for staff in different positions. At the same time, it is necessary to strengthen the judgment of the quality of literatures.
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Feb 2020
[Research and application of orthotopic DR chest radiograph quality control system based on artificial intelligence].
With the change of medical diagnosis and treatment mode, the quality of medical image directly affects the diagnosis and treatment of the disease for doctors. Therefore, realization of intelligent image quality control by computer will have a greater auxiliary effect on the radiographer's filming work. ⋯ The results demonstrate that deep learning algorithm is more accurate and efficient than the traditional image processing algorithm in the effective training of medical image big data, which explains the broad application prospect of deep learning in the medical field. This paper developed a set of intelligent quality control system for auxiliary filming, and successfully applied it to the Radiology Department of West China Hospital and other city and county hospitals, which effectively verified the feasibility and stability of the quality control system.
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Dec 2019
[Discussion and improvement methods of quantitative susceptibility mapping reconstruction].
To assess the background field removal method usually used in quantitative susceptibility mapping (QSM), and to analyze the cause of serious artifacts generated in the truncated k-space division (TKD) method, this paper discusses a variety of background field removal methods and proposes an improved method to suppress the artifacts of susceptibility inversion. Firstly, we scanned phase images with the gradient echo sequence and then compared the quality and the speed of reconstructed images of sophisticated harmonic artifact reduction for phase data (SHARP), regularization enable of SHARP (RESHARP) and laplacian boundary value (LBV) methods. Secondly, we analyzed the reasons for reconstruction artifacts caused by the multiple truncations and discontinuity of the TKD method, and an improved TKD method was proposed by increasing threshold truncation range and improving data continuity. ⋯ The results show that the reconstruction of SHARP and RESHARP are very fast, but SHARP reconstruction artifacts are serious and the reconstruction precision is not high and implementation of RESHARP is complicated. The reconstruction speed of LBV method is slow, but the detail of the reconstructed image is prominent and the precision is high. In the QSM inversion methods, the reconstruction artifact of the original TKD method is serious, while the improved method obtains good artifact suppression image and good inversion result of artifact regions.
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Oct 2019
[Construction of multi-parameter emergency database and preliminary application research].
The analysis of big data in medical field cannot be isolated from the high quality clinical database, and the construction of first aid database in our country is still in the early stage of exploration. This paper introduces the idea and key technology of the construction of multi-parameter first aid database. By combining emergency business flow with information flow, an emergency data integration model was designed with reference to the architecture of the Medical Information Mart for Intensive Care III (MIMIC-III), created by Computational Physiology Laboratory of Massachusetts Institute of Technology (MIT), and a high-quality first-aid database was built. ⋯ And based on the database, the first First-Aid Big Data Datathon event, which 13 teams from all over the country participated in, was launched. The First-Aid database provides a reference for the construction and application of clinical database in China. And it could provide powerful data support for scientific research, clinical decision making and the improvement of medical quality, which will further promote secondary analysis of clinical data in our country.
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Jun 2019
[Automatic classification method of arrhythmia based on discriminative deep belief networks].
Existing arrhythmia classification methods usually use manual selection of electrocardiogram (ECG) signal features, so that the feature selection is subjective, and the feature extraction is complex, leaving the classification accuracy usually affected. Based on this situation, a new method of arrhythmia automatic classification based on discriminative deep belief networks (DDBNs) is proposed. The morphological features of heart beat signals are automatically extracted from the constructed generative restricted Boltzmann machine (GRBM), then the discriminative restricted Boltzmann machine (DRBM) with feature learning and classification ability is introduced, and arrhythmia classification is performed according to the extracted morphological features and RR interval features. ⋯ For training sets and test sets with inconsistent data sources, a small number of training sets are extended by the active learning (AL) method, and the overall classification accuracy of the method is up to 99.31% ± 0.23%. The experimental results show the effectiveness of the method in arrhythmia automatic feature extraction and classification. It provides a new solution for the automatic extraction of ECG signal features and classification for deep learning.