Image interpolation is often required during medical image processing and analysis. Although interpolation method based on Gaussian radial basis function (GRBF) has high precision, the long calculation time still limits its application in field of image interpolation. To overcome this problem, a method of two-dimensional and three-dimensional medical image GRBF interpolation based on computing unified device architecture (CUDA) is proposed in this paper. According to single instruction multiple threads (SIMT) executive model of CUDA, various optimizing measures such as coalesced access and shared memory are adopted in this study. To eliminate the edge distortion of image interpolation, natural suture algorithm is utilized in overlapping regions while adopting data space strategy of separating 2D images into blocks or dividing 3D images into sub-volumes. Keeping a high interpolation precision, the 2D and 3D medical image GRBF interpolation achieved great acceleration in each basic computing step. The experiments showed that the operative efficiency of image GRBF interpolation based on CUDA platform was obviously improved compared with CPU calculation. The present method is of a considerable reference value in the application field of image interpolation.
ObjectiveTo compare and evaluate the discrimination, validity, and reliability of different data envelopment analysis (DEA) models for measuring the effectiveness of models by selecting different input and output indicators of the model.MethodsData from health statistical reports and pilot program of diagnosis-related groups of tertiary hospitals in Hubei Province from 2017 to 2018 were used to analyze the discrimination, content and structure validity, and reliability of the models. Six DEA models were established by enriching the details of input and output on the basis of the input and output indicators of the conventional DEA model of hospitals.ResultsFrom the view of discrimination, the results of all models were left-skewed, the cost-efficiency model had the lowest left-skewed degree (skewness coefficient: -0.14) and was the flattest (kurtosis coefficient: -1.02). From the view of structure validity, the results of the cost-efficiency model were positively correlated with total weights, outpatient visits, and inpatient visits (r=0.328, 0.329, 0.315; P<0.05). From the perspective of content validity, the interpretation of model was more consistent with theory of production after revision of input and output indicators. From the view of reliability, the cost efficiency model had the largest correlation coefficient between the data of 2017 and 2018 (r=0.880, P<0.05).ConclusionsAfter refining the input and output indicators of the DEA model, the discrimination, validity, and reliability of the model are higher, and the results are more reasonable. Using indicators such as discrimination, validity, and reliability can measure the effectiveness of the DEA model, and then optimize the model by selecting different input and output indicators.
Vena cava filter is a filter device designed to prevent pulmonary embolism caused by thrombus detached from lower limbs and pelvis. A new retrievable vena cava filter was designed in this study. To evaluate hemodynamic performance and thrombus capture efficiency after transplanting vena cava filter, numerical simulation of computational fluid dynamics was used to simulate hemodynamics and compare it with the commercialized Denali and Aegisy filters, and in vitro experimental test was performed to compare the thrombus capture effect. In this paper, the two-phase flow model of computational fluid dynamics software was used to analyze the outlet blood flow velocity, inlet-outlet pressure difference, wall shear stress on the wall of the filter, the area ratio of the high and low wall shear stress area and thrombus capture efficiency when the thrombus diameter was 5 mm, 10 mm, 15 mm and thrombus content was 10%, 20%, 30%, respectively. Meanwhile, the thrombus capture effects of the above three filters were also compared and evaluated by in vitro experimental data. The results showed that the Denali filter has minimal interference to blood flow after implantation, but has the worst capture effect on 5 mm small diameter thrombus; the Aegisy filter has the best effect on the trapping of thrombus with different diameters and concentrations, but the low wall shear stress area ratio is the largest; the new filter designed in this study has a good filtering and capture efficiency on small-diameter thrombus, and the area ratio of low wall shear stress which is prone to thrombosis is small. The low wall shear stress area of the Denali and Aegisy filters is relatively large, and the risk of thrombosis is high. Based on the above results, it is expected that the new vena cava filter designed in this paper can provide a reference for the design and clinical selection of new filters.
Objective To develop a Matlab toolbox to improve the efficiency of musculoskeletal kinematics analysis while ensuring the consistency of musculoskeletal kinematics analysis process and results. Methods Adopted the design concept of “Batch processing tedious operation”, based on the Matlab connection OpenSim interface function ensures the consistency of musculoskeletal kinematics analysis process and results, the functional programming was applied to package the five steps for scale, inverse kinematics analysis, residual reduction algorithm, static optimization analysis, and joint reaction analysis of musculoskeletal kinematics analysis as functional functions, and command programming was applied to analyze musculoskeletal movements in large numbers of patients. A toolbox called LLMKA (Lower Limbs Musculoskeletal Kinematics Analysis) was developed. Taking 120 patients with medial knee osteoarthritis as the research object, a clinical researcher was selected using the LLMKA toolbox and OpenSim to test whether the analysis process and results were consistent between the two methods. The researcher used the LLMKA toolbox again to conduct musculoskeletal kinematics analysis in 120 patients to verify whether the use of this toolbox could improve the efficiency of musculoskeletal kinematics analysis compared with using OpenSim. Results Using the LLMKA toolbox could analyze musculoskeletal kinematics analysis in a large number of patients, and the analysis process and results were consistent with the use of OpenSim. Compared to using OpenSim, musculoskeletal kinematics analysis was completed in 120 patients using the LLMKA toolbox with only 2 operations were needed to enter the patient body mass data, operating steps decreased by 99.19%, total analysis time by 66.84%, and manual participation time by 99.72%, just need 0.079 1 hour (4 minutes and 45 seconds). Conclusion The LLMKA toolbox can complete a large number of musculoskeletal kinematics analysis in patients with one click in a way that is consistent in process and results with using OpenSim, reducing the total time of musculoskeletal kinematics analysis, and liberating clinical researchers from cumbersome steps, making more energy into the clinical significance of musculoskeletal kinematics analysis results.
Mesenchymal stem cells (MSCs) are pluripotent stem cells with high self-proliferation and multidirectional differentiation potential. They also have other functions including immune regulation, paracrine and so on, playing an important role in repairing injured tissues. In recent years, a lot of research has been done on how MSCs promote skin injury repair, and a lot of progress has been made. Compared with direct injection of MSCs in the wound area, some special treatments or transplantation methods could enhance the ability of MSCs to repair skin injury. This paper mainly discusses the role of MSCs in skin injury repair and technical ways to improve its repairing capacity, and discusses the existing problems in this field and prospects for future research directions.
Objective To establish a cooperative decision-making model of county-level public hospitals, so as to freely select the best partner in different decision-making units and promote the optimal allocation of medical resources. Methods The input and output data of 10 adjacent county-level public hospitals in Henan province from 2017 to 2019 was selected. Based on the traditional data envelopment analysis (DEA) model, a generalized fuzzy DEA cooperative decision-making model with better applicability to fuzzy indicators and optional decision-making units was constructed. By inputting index information such as total number of employees, number of beds, annual outpatient and emergency volume, number of discharged patients, total income and hospital grade evaluation, the cooperation efficiency intervals of different hospitals were calculated to scientifically select the best partner in different decision-making units.Results After substituting the data of 10 county-level public hospitals in H1-H10 into the model, taking H2 hospital as an example to make cooperative decision, among the four hospitals in H1, H2, H7 and H10 of the same scale, under optimistic circumstances, the best partner of H2 hospital was H7 hospital, and the cooperation efficiency value was 1.97; in a pessimistic situation, the best partner of H2 hospital was H10 hospital, and the cooperation efficiency value was 0.98. The model had good applicability in the cooperative decision-making of county-level public hospitals. Conclusion The generalized fuzzy DEA model can better evaluate the cooperative decision-making analysis between county-level public hospitals.
Objective To explore the characteristics of exercise ventilation function in patients with chronic duration of asthma, and the correlation of cardiopulmonary exercise test and control level and conventional lung function in patients with chronic duration of asthma. Methods Seventy-three patients with chronic duration of asthma admitted from December 2021 to December 2022 were recruited in the study. The asthma control level was assessed with the asthma control test (ACT) and the patients were divided into a well-controlled group and a poorly-controlled group. Routine pulmonary function test (PFT) and cardiopulmonary exercise test (CPET) were performed in both groups, to analyze the difference of related parameters between the two groups and observe the correlation between CPET and PFT, ACT score in the patients with chronic persistent asthma. Results CPET results showed that the VE/VCO2 slope, anaerobic threshold carbon dioxide equivalent (EqCO2@AT), and physiologically ineffective peak during exercise (VD/VTpeak) were higher in the poorly-controlled group than those in the well-controlled group (all P<0.05). The peak minute ventilation (VEpeak) and tidal volume (VTpeak) of the patients in the poorly-controlled group were lower than those in the well-controlled group (both P<0.05). The peak respiratory rate (BFpeak) and respiratory reserve (BRpeak) of the two groups were not significantly different (both P>0.05). The results of correlation analysis showed that the VE/VCO2 slope, EqCO2@AT, VD/VTpeak were negatively correlated with ACT score, and VEpeak was positively correlated with FVC%pred and MMEF%pred in the patients with chronic persistent asthma. BRpeak was positively correlated with FEV1%pred, FEV1/FVC%pred, MMEF%pred in routine pulmonary function. Multivariate logistic regression analysis showed that the increase of VE/VCO2 slope and VD/VTpeak were independent risk factors for poor asthma control (P<0.05). Conclusions Patients with poorly-controlled asthma have decreased exercise ventilatory function, mainly showing decreased ventilation and tidal volume during peak exercise and decreased ventilatory efficiency. There is some correlation between exercise ventilatory function and conventional lung function of control level in patients with chronic duration of asthma. The relevant indicators of ventilation efficiency in CPET have suggestive significance for asthma that is not well controlled, so it is necessary to carry out CPET in patients with asthma to improve the comprehensive evaluation of asthma.
With the rapid development of artificial intelligence (AI) technology, its application in hospital management is gradually becoming an important means to improve operational efficiency and the quality of patient health care. This article systematically explores the multidimensional applications of AI in hospital management, including medical services, administration, patient engagement and experience. Through in-depth analysis, the paper evaluates the potential of AI in these areas, especially the significant effect in improving operational efficiency and optimising patient healthcare services. However, the application of AI also faces many challenges, such as data privacy issues, algorithmic bias, operational management, and economic factors. This article not only identifies these challenges, but also provides specific inspiration and recommendations for hospital management in China, emphasises the importance of adaptability and continuous learning, and calls on hospital administrators to actively embrace change in order to achieve both improved patient health outcomes and operational efficiency.
ObjectiveTo measure the operational efficiency and explore the phenomenon of the economy of scale in secondary public general hospitals of China for improving the health service efficiency.MethodsFrom February to August 2019, the data set of two input indicators (the number of employees and actual open beds) and two output indicators (the numbers of outpatients and discharges) in 511 secondary general hospitals of Shandong, Anhui, Shanxi, Hubei and Hainan provinces in 2018 were collected for data envelopment analysis. The analysis processes were three folds: First, the technical efficiency, pure technical efficiency, scale efficiency and scale compensation status of the sample hospitals were calculated respectively. Second, the comparative analysis of efficiency value and scale compensation status was carried out in 5 groups according to the bed scale. Finally, the input and output projection analysis was carried out on the ineffective decision making units.ResultsThe medians of technical efficiencies, pure technical efficiencies, and scale efficiencies of the 511 secondary general hospitals were 0.472, 0.531, and 0.909, respectively. In the 511 hospitals, 493 hospitals (96.5%) were in ineffective state, of which 321 hospitals (62.8%) were in the state of decreasing return to scale. The staff redundancy of the group with beds >100 and ≤300 was 23.86%, and its service quantity could be increased by 39.37%.ConclusionsThe overall operating efficiencies are inefficiency in secondary general hospitals of China and the optimal scale of actual open beds is between 300 and 500 beds from the perspective of scale efficiency.
ObjectiveTo summarize the evaluation indexes of health resource utilization efficiency in enhanced recovery after surgery (ERAS) , so as to provide reference for the construction of evaluation index system.MethodLiteratures on the allocation, utilization, and efficiency of ERAS health resources at home and abroad in recent years were reviewed and analyzed.ResultsAt present, no systematic evaluation index system of ERAS health resources utilization efficiency had been formed at home and abroad. In the research, the formulation direction of input index mainly included ERAS human resources allocation and material resources allocation, while the formulation direction of output index mainly included ERAS medical resources utilization.ConclusionsThe evaluation system of ERAS health resources utilization efficiency is not perfect and the research scope of its index system is too small, which restricts the standardization promotion of ERAS. It is an urgent problem to construct a scientific evaluation index system for ERAS health resources utilization efficiency.