Heart sound signal is a kind of physiological signal with nonlinear and nonstationary features. In order to improve the accuracy and efficiency of the phonocardiogram (PCG) classification, a new method was proposed by means of support vector machine (SVM) in which the complete ensemble empirical modal decomposition with adaptive noise (CEEMDAN) permutation entropy was as the eigenvector of heart sound signal. Firstly, the PCG was decomposed by CEEMDAN into a number of intrinsic mode functions (IMFs) from high to low frequency. Secondly, the IMFs were sifted according to the correlation coefficient, energy factor and signal-to-noise ratio. Then the instantaneous frequency was extracted by Hilbert transform, and its permutation entropy was constituted into eigenvector. Finally, the accuracy of the method was verified by using a hundred PCG samples selected from the 2016 PhysioNet/CinC Challenge. The results showed that the accuracy rate of the proposed method could reach up to 87%. In comparison with the traditional EMD and EEMD permutation entropy methods, the accuracy rate was increased by 18%–24%, which demonstrates the efficiency of the proposed method.
Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine.
In this paper, a deep learning method has been raised to build an automatic classification algorithm of severity of chronic obstructive pulmonary disease. Large sample clinical data as input feature were analyzed for their weights in classification. Through feature selection, model training, parameter optimization and model testing, a classification prediction model based on deep belief network was built to predict severity classification criteria raised by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We get accuracy over 90% in prediction for two different standardized versions of severity criteria raised in 2007 and 2011 respectively. Moreover, we also got the contribution ranking of different input features through analyzing the model coefficient matrix and confirmed that there was a certain degree of agreement between the more contributive input features and the clinical diagnostic knowledge. The validity of the deep belief network model was proved by this result. This study provides an effective solution for the application of deep learning method in automatic diagnostic decision making.
Objective To review the latest progress in classification system of thoracolumbar fractures and its surgical treatment with posterior approaches. Methods Recent l iterature about classification system of thoracolumbar fractures and its surgical treatment was reviewed. Results For the treatment of thoracolumbar fracture, the surgeon first should decide whether the surgical treatment was necessary. Recently, a new classification system had been developed to help the surgeon make the right decision. The surgical methods included short segment internal fixation and long segment internalfixation with or without fusion, and minimally invasive internal fixation. Conclusion The progress in the surgical treatmentof thoracolumbar fracture will help spinal surgeon decide the necessary surgery beneficial for the patients. The most appropriate and effective surgical method with the minimum damage should be used to treat the fracture. The advantages of non-fusion surgical treatment still need a further study.
ObjectiveTo analyze the clinical character of uveitis in second hospital of Jilin university. MethodsRetrospectively analyze the clinical data of uveitis patients referred to from Second Hospital of Jilin University from September 2009 to September 2014. According to anatomical location, the manifestation of these uveitis patients were divided into anterior uveitis, panuveitis, intermediate uveitis and posterior uveitis. To discuss the possible causes of these patients according to the general information and relevant clinical laboratory examinations results. ResultsThere were 1215 cases in this study, which included 587 male, accounting for 48.31%; and 628 female, accounting for 51.69%. The ratio of male-to-female was 0.93:1. The range of the age of these patients was from 4 to 91 years old. The mean age of these patients at the onset of these disease was (41.43±14.20) years. Of the 1215 cases, 40 male and 43 female were younger than 20 years. The ratio of male-to-female was 0.93:1; 412 male and 396 female were between 21 and 50 years old. The ratio of male-to-female was 1.04:1; 135 male 189 female were older than 50 years. The ratio of male-to-female was 0.71:1. There were 572 cases of anterior uveitis, accounting for 47.08%; 527 cases of panuveitis, accounting for 43.37%; 52 cases of intermediate uveitis, accounting for 4.28%; 64 cases of posterior uveitis, accounting for 5.27%. 703 cases had etiological diagnosis according to the clinical character and the auxiliary results, accounting for 57.68%. Vogt-koyanagi Haradal (VKH) syndrome, ankylosing spondylitis associated with uveitis and Behçet's disease were the common entity, accounting for 30.44%, 19.77% and 14.22% respectively. ConclusionsThe mean age of these patients in this study was older, compared to other reports. Female patients were more than male, especially in these patients older than 50 years. VKH syndrome, ankylosing spondylitis associated with uveitis and Behçet's disease were the common entities.
OBJECTIVE: To investigate the characteristics and the pathologic classification of electrical-injury nerve using somatosensory evoked potential(SEP) technique. METHODS: SEP were detected and evaluated in 12 cases with electrical-injury nerve during operation, electrical stimulation was commenced from distal side of nerve where the structure of nerve looks normal under operating microscope, up to proximal side until evoking out a stable SEP predeterminate virtual value. Pathological examination and the following functional evaluation were compared with the values of SEP. RESULTS: At the site of nerve looking normal under operating microscope, perineurium appears normal or slightly thicken. But there are obvious fibrosis and fibrotic proliferation between fascicular and intrafascicular. Vessel plexus is not seen. At SEP stabilizely evoked site, nervous construction is normal, there are visible interfascicular vessel plexus and connective tissue appears loose. Comparing SEP values with pathological section, amplitude and latency of SEP is positively correlative with the quality of nerve. Eight cases repaired with SEP technique to select the anastomosis site for nerve transplantation were followed up, two-point discrimination reached grade III (America hand surgery association criterion) within 62.5% cases. CONCLUSION: SEP technique is valuable method for functional evaluation of electrical- injury nerve which has a complicated pathology. The pathology of electrical-injury nerve can be classified into 4 types, type A: fibrosis of nerve; type B: nerve looking normal under operation microscope, perineurium appears thicken, and there are obvious fibrosis and fibrotic proliferation between fascicular and intrafascicular, vessel plexus is rarely to see; type C: nerve looks normal, lymphocyte infiltration exists and it is obvious that there are many physalis-like, retrogressive construction in the section; type D: nervous construction is normal, there are visible interfascicular vessel plexus, and connective tissue appears loose, SEP always can be stably evoked.
Stem cells belong to a subgroup of undifferentiated cells in organisms, which has the features of proliferation, self maintaining, and self renewal, and may produce plentiful filial generation with functions. According to the researches on embryonic stem cells, retinal stem cells in adults, and intraocular tumor stem cells, stems cells exist in human embryo, adult retina, and also intraocular tumors like retinoblastoma and choroidal melanoma. Different stem cells transplanted into subretinal interspace or vitreous cavity may differentiate into structure of neurone or retina. Stem cells may become a newest target of the researches on pathogenesis and treatment of diseases. (Chin J Ocul Fundus Dis, 2007, 23: 83-86)
ObjectiveTo encourage clinicians to code the major diagnosis of diseases, in order to improve the correct rate of disease major diagnosis coding. MethodsWe analyzed the data of major diagnostic codes by clinicians from January 2012 to June 2013. The group leader of the clinical treatment was designated to be responsible for the disease coding. Disease coders introduced knowledge of international classification of diseases to the clinical department according to the different characteristics of disease in each department and communicated with clinicians on the problems of disease coding. Then, we tried to find out whether this method could improve the correct rate of major diagnosis coding of diseases. ResultsThe rate of disease major coding by clinicians of the whole hospital and pilot departments increased from 94.081% to 98.301%. The correct rate of disease major coding decreased from 75.824% to 67.483% and then reached 81.893%. The correct rate of disease major coding of the Department of Hematology was 83.824% in August 2012 and then decreased with the lowest rate of 68.025%; and the correct rate of disease major coding of the Department of Orthopedics increased rapidly and reached 90% in September 2012. ConclusionsThrough the leader of the clinical treatment being responsible for the disease coding and encouraging clinicians to code the main diagnosis of diseases, the accurate of disease major diagnosis coding has improved. Strengthening the communication between clinical and Medical Record Departments can help our hospital improve the quality of disease major diagnosis coding continuously.