An exploration of new methods for metabolic syndrome examination by infrared thermography and knowledge mining.

Metabolic syndrome (MS) is a clinical syndrome with multiple metabolic disorders. As the diagnostic criteria for MS still lacking of imaging laboratory method, this study aimed to explore the differences between healthy people and MS patients through infrared thermography (IRT). However, the observation region of the IRT image is uncertain, and the research tried to solve this problem with the help of knowledge mining technology.

[A preliminary study on the diagnostic value of infrared thermography in children with idiopathic thrombocytopenic purpura].

Idiopathic thrombocytopenic purpura (ITP) is a common bloody disease with a high incidence in children, but its diagnostic method is exclusive diagnosis, and the existing detection techniques are mostly invasive, which may cause secondary injury to patients and also may increase the risk of disease. In order to make up for the lack of the detection method, this study made a preliminary exploration on the diagnosis of children's ITP from the perspective of infrared thermography. In this study, a total of 11 healthy children and 22 ITP children's frontal infrared thermal images were collected, and the pattern characteristic (PFD), average temperature (Troi) and maximum temperature (MAX) characteristics of 7 target areas were extracted.

A research on syndrome element differentiation based on phenomenology and mathematical method.

Background: As an empirical medical system independent of conventional Western medicine (CWM), over thousands of years, traditional Chinese medicine (TCM) has established its own unique method of diagnosis and treatment. The perspective of holism and system in TCM is essentially different from the view of Reductionism in CWM. With the development of modern science and technology, the restriction of reductionism is more and more prominent, and researchers begin to pay more attention to holistic thinking in TCM.

[MicroRNA Target Prediction Based on Support Vector Machine Ensemble Classification Algorithm of Under-sampling Technique].

Considering the low accuracy of prediction in the positive samples and poor overall classification effects caused by unbalanced sample data of MicroRNA (miRNA) target, we proposes a support vector machine (SVM)-integration of under-sampling and weight (IUSM) algorithm in this paper, an under-sampling based on the ensemble learning algorithm. The algorithm adopts SVM as learning algorithm and AdaBoost as integration framework, and embeds clustering-based under-sampling into the iterative process, aiming at reducing the degree of unbalanced distribution of positive and negative samples. Meanwhile, in the process of adaptive weight adjustment of the samples, the SVM-IUSM algorithm eliminates the abnormal ones in negative samples with robust sample weights smoothing mechanism so as to avoid over-learning.

[Automatic Classification of Epileptic Electroencephalogram Signal Based on Improved Multivariate Multiscale Entropy].

Traditional sample entropy fails to quantify inherent long-range dependencies among real data. Multiscale sample entropy (MSE) can detect intrinsic correlations in data, but it is usually used in univariate data. To generalize this method for multichannel data, we introduced multivariate multiscale entropy into multiscale signals as a reflection of the nonlinear dynamic correlation.

[Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue.

[Research on the methods for inter-class distinctive feature selection for leucocyte recognition based on attribute hierarchical relationship].

To increase efficiency of automated leucocyte pattern recognition using lower feature dimensions, a novel inter-class distinctive feature selection method for chromatic leucocyte images was proposed based on attribute hierarchical relationship. According to the attribute constraints in formal concept analysis, we established a knowledge representation and discovery method based on the hierarchical optimal diagram by defining attribute value and visual representation of optimized hierarchical relationship. It was applied to human peripheral blood leucocytes classification and 12 distinctive attributes were simplified from 60 inter-class attributes, which contributes significantly to reduced feature dimensions and efficient inter-class feature classification.

Deep first formal concept search.

The calculation of formal concepts is a very important part in the theory of formal concept analysis (FCA); however, within the framework of FCA, computing all formal concepts is the main challenge because of its exponential complexity and difficulty in visualizing the calculating process. With the basic idea of Depth First Search, this paper presents a visualization algorithm by the attribute topology of formal context. Limited by the constraints and calculation rules, all concepts are achieved by the visualization global formal concepts searching, based on the topology degenerated with the fixed start and end points, without repetition and omission.

[Objective assessment of facial paralysis using infrared thermography and formal concept analysis].

This paper presented a novel approach to objective assessment of facial nerve paralysis based on infrared thermography and formal concept analysis. Sixty five patients with facial nerve paralysis on one side were included in the study. The facial temperature distribution images of these 65 patients were captured by infrared thermography every five days during one-month period.

[Application of semi-supervised sparse representation classifier based on help training in EEG classification].

Electroencephalogram (EEG) classification for brain-computer interface (BCI) is a new way of realizing human-computer interreaction. In this paper the application of semi-supervised sparse representation classifier algorithms based on help training to EEG classification for BCI is reported. Firstly, the correlation information of the unlabeled data is obtained by sparse representation classifier and some data with high correlation selected.

[A leukocyte pattern recognition based on feature fusion in multi-color space].

To solve the ineffective problem of leukocytes classification based on multi-feature fusion in a single color space, we proposed an automatic leukocyte pattern recognition by means of feature fusion with color histogram and texture granular in multi-color space. The interactive performance of three color spaces (RGB, HSV and Lab), two features (color histogram and texture granular) and four similarity measured distance metrics (normalized intersection, Euclidean distance, chi2-metric distance and Mahalanobis distance) were discussed. The optimized classification modes of high precision, extensive universality and low cost to different leukocyte types were obtained respectively, and then the recognition system of tree-integration of the optimized modes was established.

[Research on compatibility of prescription of TCP based on the principle of attribute hierarchical graph].

On the basis of the theory of formal concept analysis (FCA), a new method for generation of an attribute hierarchical graph is proposed in this paper. This method can solve the problems of how to mine and express classification knowledge and rules in compatibility of prescription. In this paper, we view prescriptions as objects that possess certain attributes of the named drugs.

[Objective assessment of facial paralysis using local binary pattern in infrared thermography].

Facial paralysis is a frequently-occurring disease, which causes the loss of the voluntary muscles on one side of the face due to the damages the facial nerve and results in an inability to close the eye and leads to dropping of the angle of the mouth. There have been few objective methods to quantitatively diagnose it and assess this disease for clinically treating the patients so far. The skin temperature distribution of a healthy human body exhibits a contralateral symmetry.

[Research progress in using functional near-infrared spectroscopy for monitoring depth of anesthesia].

Intra-operation monitoring depth of anesthesia is an important method to insure the quality and safety of clinical anesthesia. As a noninvasive brain function monitoring technology, functional near-infrared spectroscopy can provide objective and reliable brain activity monitoring and imaging in real time. The characteristic of this technique is highly suitable for interrelated research on depth of anesthesia monitoring.

[Research on automatic external defibrillator based on DSP].

Electrical defibrillation is the most effective way to treat the ventricular tachycardia (VT) and ventricular fibrillation (VF). An automatic external defibrillator based on DSP is introduced in this paper. The whole design consists of the signal collection module, the microprocessor controlingl module, the display module, the defibrillation module and the automatic recognition algorithm for VF and non VF, etc.

[Symbolic dynamics analysis of epileptic EEG signals of the rat].

Epilepsy is a common chronic neurological disease, which is caused by excessive brain neuron discharge. The epileptic seizure has the characteristic of abruptness and reiteration. Prediction of seizures has great significance for patients to take timely and effective clinical measures.

[Using infrared thermal asymmetry analysis for objective assessment of the lesion of facial nerve function].

The skin temperature distribution of a healthy human body exhibits a contralateral symmetry. Some lesions of facial nerve function are associated with an alteration of the thermal distribution of the human body. Since the dissipation of heat through the skin occurs for the most part in the form of infrared radiation, infrared thermography is the method of choice to capture the alteration of the infrared thermal distribution.

[Application of the quality evaluation of traditional Chinese herbal medicines using chromatography of fingerprints].

Chromatography of fingerprint as an important tool has been used in identification and quality control of herbal medicines, and it is gaining more and more attention. Among the various methods, chromatography gradually becomes the mainstream for its characteristics. This paper describes the techniques of chromatography of fingerprint including pretreatments for sample data set, the establishment of chromatographic fingerprint and fingerprint visualization.

[Identification of special quality eggs with NIR spectroscopy technology based on symbol entropy feature extraction method].

Fast, nondestructive and accurate identification of special quality eggs is an urgent problem. The present paper proposed a new feature extraction method based on symbol entropy to identify near infrared spectroscopy of special quality eggs. The authors selected normal eggs, free range eggs, selenium-enriched eggs and zinc-enriched eggs as research objects and measured the near-infrared diffuse reflectance spectra in the range of 12 000-4 000 cm(-1).

[Extraction method of the visual graphical feature from biomedical data].

The vector space transformations such as principal component analysis (PCA), linear discriminant analysis (LDA), independent component analysis (ICA) or the kernel-based methods may be applied on the extracted feature from the field, which could improve the classification performance. A barycentre graphical feature extraction method of the star plot was proposed in the present study based on the graphical representation of multi-dimensional data. The feature order question of the graphical representation methods affecting the star plot was investigated and the feature order method was proposed based on the improved genetic algorithm (GA).

[Anomaly of infrared thermal radiation intensity on unilateral mild to moderate Bell's palsy].

Bell's palsy is a kind of facial nerve diseases with a high incidence, and the patients who get the disease the first time predominate in the patients who suffer mildly or moderately. The aim of the present study is to explore a novel assessment for Bell's palsy objectively and noninvasively based on infrared thermal image. As the acupoints on the face are approximately bilateral symmetric, the acupoints on the affected side were chosen as the experimental group, while the same ones on the other side as the control group.

[Application of ozone concentration detection in the medical aspects and its development].

This article introduces some commonly used methods of ozone concentration detection, including chemical method, UV absorption method, and electrochemical method etc., introduces the latest four ozone concentration sensors, and summarizes the advantages and disadvantages of each method. In addition, the article emphatically introduces the ozone's applications and development in the medical aspects.

[Cardiac arrhythmia classification based on multi-features and support vector machines].

To solve the problem of cardiac arrhythmias classification, we proposed a novel algorithm based on the multi-feature fusion and support vector machines (SVM). Kernel independent component analysis (KICA) was used to extract nonlinear features and wavelet transform (WT) was used to extract time-frequency features. Combining these features could include more information about the disease.

[Research on ECG signal analysis based on the cloudy model theory].

The characteristics of electrocardiogram (ECG) signal are fuzzy and random, so that they are difficult for automatic analysis and diagnosis. To solve this problem, an uncertainties transformation model-Cloud Model, which is a fusion of qualitative and quantitative information, was tried to use to analyze the ECG signal. The model fusions the characters of fuzzy and random, just suit to the ECG automatic analysis and diagnosis system.