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.
In computer-aided medical diagnosis, obtaining labeled medical image data is expensive, while there is a high demand for model interpretability. However, most deep learning models currently require a large amount of data and lack interpretability. To address these challenges, this paper proposes a novel data augmentation method for medical image segmentation. The uniqueness and advantages of this method lie in the utilization of gradient-weighted class activation mapping to extract data efficient features, which are then fused with the original image. Subsequently, a new channel weight feature extractor is constructed to learn the weights between different channels. This approach achieves non-destructive data augmentation effects, enhancing the model's performance, data efficiency, and interpretability. Applying the method of this paper to the Hyper-Kvasir dataset, the intersection over union (IoU) and Dice of the U-net were improved, respectively; and on the ISIC-Archive dataset, the IoU and Dice of the DeepLabV3+ were also improved respectively. Furthermore, even when the training data is reduced to 70 %, the proposed method can still achieve performance that is 95 % of that achieved with the entire dataset, indicating its good data efficiency. Moreover, the data-efficient features used in the method have interpretable information built-in, which enhances the interpretability of the model. The method has excellent universality, is plug-and-play, applicable to various segmentation methods, and does not require modification of the network structure, thus it is easy to integrate into existing medical image segmentation method, enhancing the convenience of future research and applications.
Objective To analyze the dynamic efficiency of township hospitals. Methods Based on the DEA-Malmquist index, this research analyzed the change of the total factor productivity indices and the decomposition items of 281 township hospitals in Hunan province with panel data from 2000 to 2008. Results Among 281 township hospitals, less than half increased their scale efficiency, while more than half increased their total factor productivity, technology, whole efficiency and technical efficiency. Increasing technology and whole efficiency was the best way to improve total factor productivity. Besides, increasing technical efficiency and scale efficiency was the best way to improve whole efficiency. Conclusions The improvement of scale efficiency is key to developing the central township hospitals, while the improvement of technology is the key to developing general township hospitals.
The aim of this study is to explore the effects of continuous theta-burst transcranial magnetic stimulation (cTBS) on functional brain network in emotion processing. Before and after the intervention of cTBS over left dorsolateral prefrontal cortex (DLPFC) of ten participants who were asked to perform the emotion gender recognition task, we recorded their scalp electroencephalograms (EEG). Then we used the phase synchronization of EEG to measure the connectivity between two nodes. We then calculated the network efficiency to describe the efficiency of information transmission in brain regions. Our research showed that after the intervention of cTBS and the stimulation of the emotion face picture, there was an obvious enhancement in the event-related spectral perturbation after stimuli onset in beta band in 100–300 ms. Under the stimulation of different emotion picture, the values of global phase synchronization for negative and neutral stimuli were enhanced compared to positive ones. And the increased small-worldness was found in emotional processing. In summary, based on the effect of activity change in the left DLPFC on emotion processing brain network, the emotional processing mechanism of brain networks were preliminary explored and it provided the reference for the research of emotion processing brain network in the future.
There are few researches on the modulation effect of transcranial direct current stimulation(tDCS) on complex spatial cognition. Especially, the influence of tDCS on the neural electrophysiological response in spatial cognition is not yet clear. This study selected the classic spatial cognition task paradigm (three-dimensional mental rotation task) as the research object. By comparing the changes in behavior and event-related potentials in different modes of tDCS before, during and after the application of tDCS, this study analyzed the behavioral and neurophysiological effects of tDCS on mental rotation. The comparison between active-tDCS and sham-tDCS showed no statistically significant difference in behavior between different stimulation modes. Still, the changes in the amplitudes of P2 and P3 during the stimulation were statistically significant. Compared with sham-tDCS, the amplitudes of P2 and P3 in active-tDCS mode showed a greater decrease during the stimulation. This study clarifies the influence of tDCS on the event-related potentials of the mental rotation task. It shows that tDCS may improve the brain information processing efficiency during the mental rotation task. Also, this study provides a reference for an in-depth understanding and exploration of the modulation effect of tDCS on complex spatial cognition.
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.
Anxiety disorder is a common emotional handicap, which seriously affects the normal life of patients and endangers their physical and mental health. The prefrontal cortex is a key brain region which is responsible for anxiety. Action potential and behavioral data of rats in the elevated plus maze (EPM) during anxiety (an innate anxiety paradigm) can be obtained simultaneously by using the in vivo and in conscious animal multi-channel microelectrode array recording technique. Based on maximum likelihood estimation (MLE), the action potential causal network was established, network connectivity strength and global efficiency were calculated, and action potential causal network connectivity pattern of the medial prefrontal cortex was quantitatively characterized. We found that the entries (44.13±6.99) and residence period (439.76±50.43) s of rats in the closed arm of the elevated plus maze were obviously higher than those in the open arm [16.50±3.25, P<0.001; (160.23±48.22) s, P<0.001], respectively. The action potential causal network connectivity strength (0.017 3±0.003 6) and the global efficiency (0.044 2±0.012 8) in the closed arm were both higher than those in the open arm (0.010 4±0.003 2, P<0.01; 0.034 8±0.011 4, P<0.001), respectively. The results suggest that the changes of action potential causal network in the medial prefrontal cortex are related to anxiety state. These data could provide support for the study of the brain network mechanism in prefrontal cortex during anxiety.
ObjectiveTo explore the value of magnetic resonance diffusion weighted imaging (DWI) in preoperative Bismuth-Corlette classification of hilar cholangiocarcinoma (HCCA). MethodsA total of 53 HCCA patients confirmed by postoperative pathology were retrospectively included. The accuracy of two sequence combinations, namely dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) + magnetic resonance cholangiopancreatography (MRCP) and DCE-MRI + MRCP + DWI, in evaluating the longitudinally involved bile duct segments and Bismuth-Corlette classification of HCCA was compared. Additionally, the correlation between apparent diffusion coefficient (ADC) values and tumor Bismuth-Corlette classification as well as degree of differentiation was analyzed. ResultsThere were 318 bile duct segments in 53 HCCA patients. The accuracy rate of DCE-MRI + MRCP was 93.7% (298/318), the sensitivity was 91.5% (161/176), and the specificity was 96.5% (137/142). The accuracy rate of DCE-MRI + MRCP + DWI was 96.5% (307/318), the sensitivity was 96.0% (169/176), and the specificity was 97.2% (138/142). Receiver operating characteristic (ROC) curve analysis showed that the area under the ROC curve (AUC) of DCE-MRI + MRCP + DWI was 0.966 [95%CI (0.940, 0.983), P＜0.001], and its diagnostic efficacy was superior to that of DCE-MRI + MRCP [AUC=0.940, 95%CI (0.908, 0.963), P＜0.001]. The DeLong test indicated a statistically significant difference in AUC between the two sequences (Z=2.633, P＜0.01). The accuracy rates of preoperative Bismuth-Corlette classification of HCCA evaluated by DCE-MRI + MRCP and DCE-MRI + MRCP + DWI were 86.8% (46/53) and 94.3% (50/53), respectively. After adding the DWI sequence, the consistency between Bismuth-Corlette classification results and surgical pathological classification results (Kappa=0.922, P<0.001) was higher than that of DCE-MRI + MRCP sequence (Kappa=0.820, P<0.001), with a statistically significant difference (χ2=160.370, P<0.001). In addition, the ADC value of HCCA was negatively correlated with tumordegree of differentiation (rs=–0.524, P<0.001), but had no significant correlation with its Bismuth-Corlette classification (rs=–0.058, P=0.682). ConclusionsDCE-MRI + MRCP + DWI sequence can effectively improve the accuracy in preoperative evaluation of the involvement of bile duct segments and Bismuth-Corlette classification of HCCA, which provides guidance for precise preoperative surgical planning in clinical practice. In addition, the ADC value can provide additional information required for non-invasive preoperative prediction of the prognosis of HCCA patients.
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.
ObjectiveTo investigate the distribution, service volume, and medical efficiency of private general hospitals in Sichuan Province to provide references for optimizing the allocation of health resources in Sichuan Province. MethodsUsing the 2020 data from private general hospitals above the second level in 18 cities and states in Sichuan Province, this study calculated the market concentration and competitiveness with the Herfindahl-Hirschman index (HHI). A three-stage data envelopment analysis (DEA) model was employed to eliminate environmental variables and random errors for hospital efficiency analysis. Influencing factors were conducted using a Tobit regression model. ResultsThe HHI indices for the number of licensed (assistant) physicians, beds, and total consultations in each city and state were below 1 000, indicating a low concentration market. The comprehensive technical efficiency, pure technical efficiency, and scale efficiency of private general hospitals above the second level in Sichuan Province were 0.534, 0.661, and 0.806, respectively, after the three-stage DEA analysis. The number of practicing (assistant) physicians was negatively correlated with scale efficiency. the number of beds was negatively correlated with pure technical efficiency. The total number of consultations showed a positive correlation with overall technical efficiency, pure technical efficiency, and scale efficiency. ConclusionThe provincial private hospital market exhibits low concentration competition. Differences in efficiency exist among various regions, grades, and hospital types. Market competition in resource allocation promotes the improvement of pure technological efficiency and scale efficiency. Market share competition hinders the improvement of comprehensive technical efficiency, pure technical efficiency, and scale efficiency.
