Objective To construct a framework for hospital modernization evaluation based on capability development. Methods In accordance with the theories for the sustainable development of the hospital and the results in the research on the development mechanism of the capability-oriented hospital and giving consideration both to the development level of the hospital and the driving force of its internal development, a framework for hospital modernization evaluation was designed from both the horizontal and vertical dimensions. Results A multidimensional, multilevel, and multi-index framework for hospital modernization evaluation was constructed. Conclusion The framework for hospital modernization evaluation is capable of evaluating hospital development from different dimensions and levels and reflecting the modernization level of the hospital and the mechanism of its internal driving force, thus more effectively guiding hospital modernization.

Heart sounds are highly valuable to the clinical diagnoses of most cardiovascular diseases, so the analysis of phonocardiographic signals is helpful to diagnosing cardiovascular diseases clinically. Phonocardiographic signals are non-stable, so it is necessary to choose appropriate method in time-frequency analysis. The traditional method such as Fourier Transform is dissatisfactory. Continuous Wavelet Transform (CWT) and Matching (MPM) Pursuit Method are both effective methods. They can be used to extract and cluster the characteristics of the signals. By analysis and comparison, the two methods showed the advantages over traditional methods. Additionally, their respective merits and demerits are indicated.
Algorithms ; Fourier Analysis ; Heart Sounds ; Humans ; Phonocardiography ; Signal Processing, Computer-Assisted

Independent component analysis (ICA) is a novel method developed in recent years for Blind Source Separation. In this paper, the phonocardiogram (PCG) was separated into three components by applying ICA. The basic principle of ICA was introduced in this paper. A fast and robust fixed-point algorithm for ICA was used to analyze PCG signals in this study. The experiments showed that ICA could separate the components of heart sounds from PCG signals successfully.
Algorithms ; Heart Sounds ; Humans ; Phonocardiography ; methods ; Principal Component Analysis ; Signal Processing, Computer-Assisted