Counting the average number and standard error or standard deviation by popular method of 3 groups also leads to correct results as using Microsoft Excel software. When using Summary Statistics in Descriptive Statistics, we have average value, standard error, standard deviation and other results, in which there was a sample variance. If 2 variances of 2 samples were the similar, t test has been used. Thus, using Microsoft Excel software, we’ll have specific p value. From that, we could infer the greater or smaller results
Statistics Computer

Biological data and analysis tools are accumulated in distributed databases and web servers. For this reason, biologists who want to find information from the web should be aware of the various kinds of resources where it is located and how it is retrieved. Integrating the data from heterogeneous biological resources will enable biologists to discover new knowledge across the specific domain boundaries from sequences to expression, structure, and pathway. And inevitably biological databases contain noisy data. Therefore, consensus among databases will confirm the reliability of its contents. We have developed WeSAT that integrates distributed and heterogeneous biological databases and analysis tools, providing through Web Services protocols. In WeSAT, biologists are retrieved specific entries in SWISS-PROT/EMBL, PDB, and KEGG, which have annotated information about sequence, structure,and pathway. And further analysis is carried by integrated services for example homology search and multiple alignments. WeSAT makes it possible to retrieve real time updated data and analysis from the scattered databases in a single platform through Web Services.
Computer Communication Networks ; Consensus ; Statistics as Topic*

Due to the insufficiency in colposcopy image database collection in china, a novel image database is developed and it will be the basis of a computer-aided-diagnosis system for colposcopy. An improved search algorithm of color is designed based on the current content-based image retrieval algorithms for the characteristics of colposcopy images. This algorithm is authenticated by more than one hundred of clinical pictures with primary satisfactory result.
Algorithms ; Colposcopy ; statistics & numerical data ; Databases, Factual ; Image Interpretation, Computer-Assisted ; methods ; User-Computer Interface

To correctly classify EEG with different mental tasks, a new learning algorithm for Evolving Cascade Neural Networks (ECNNs) is described to avoid over-fitting of a neural network due to noise and redundant features. The learning algorithm calculates the value of a fitness function on validate set and accordingly updates the connection weights on training set. The learning algorithm uses the regularity criterion for selecting the neurons with relevant connection. If the value Cr calculated for the rth neuron is less than the value Cr-1 calculated for the previous (r-1) neuron, the features that feed the rth neuron are relevant, else they are irrelevant. An ECNN starts to learn with one input node and then, adding new inputs as well as new hidden neurons, evolves it. The trained ECNN has a nearly minimal number of input and hidden neurons as well as connections. The algorithm is applied to classify EEG with two mental tasks. The trained ECNN has correctly classified 83.1% of the testing segments. It shows a better result, compared with a standard BP network.
Algorithms ; Electroencephalography ; methods ; statistics & numerical data ; Humans ; Neural Networks (Computer) ; Signal Processing, Computer-Assisted

Detrended fluctuation analysis (DFA) is fit for studies on the long-range exponential correlations of non-stationary time serial. In this paper, for elucidating the characteristics of different sleep stages, DFA is adopted to analyze the physiological data collected during sleep. The parameters such as electroencephalogram (EEG), R-R interval sequence and stroke volume (SV) are analyzed, and the scaling exponent a is calculated. The experimental results reveal that the values of a differ much in different sleep stages,that the rules of EEG and SV are alike, that alpha increases with the deepening of sleep, but in inverse for R-R interval sequence that alpha decreases with the deepening of sleep. These indicate that the method of DFA is practical in the analysis of physiological parameters.
Data Interpretation, Statistical ; Electrocardiography ; statistics & numerical data ; Electroencephalography ; statistics & numerical data ; Humans ; Polysomnography ; Signal Processing, Computer-Assisted ; Sleep Stages ; physiology

Electrocardiogram (ECG) signal is important for physician to diagnose diseases. Various existing techniques on ECG classification have been reported. Generally, these techniques classify only two or three arrhythmias and need significantly long processing time. A new algorithm based on Support vector machine (SVM) is presented to solve the problem in this paper, which has been successfully applied to the classification of ECG. And in this paper are clarified the fundamental ideas of the classification of ECG based on SVM. Compared with the traditional neural network, this method is superior to it in theory. Because this new method deals with the minimization of the test samples, not the training samples.
Algorithms ; Artificial Intelligence ; Diagnosis, Computer-Assisted ; methods ; Electrocardiography ; methods ; statistics & numerical data ; Humans ; Models, Statistical ; Signal Processing, Computer-Assisted

This paper presents a typical Clinical Information System for ICU and its design and implementation. This system is able to capture and archive vital data from the monitor network, providing a whole digital solution in ICU. These vital data can be used in quantitative analysis in the computer-assisted decision support.
Decision Making, Computer-Assisted ; Information Systems ; Intensive Care Units ; Monitoring, Physiologic ; statistics & numerical data ; Software Design

OBJECTIVETo develop the prediction model of acute gastrointestinal injury (AGI) classification of critically ill patients.

METHODSThe binary channel gastrointestinal sounds (GIS) monitor system was used to gather and analyze the GIS of 60 consecutive critically ill patients who were admitted in Critical Care Medicine of PLA General Hospital from April 2015 to November 2015 (patients with chronic gastrointestinal disease or history of gastrointestinal surgery were excluded). Meanwhile, the AGI grades were evaluated according to the ESICM guidelines of AGI grading system. Correlations between GIS and AGI classification were examined with Spearman rank correlation. Then principal component analysis was performed on the significantly correlated parameters after standardization. The top 3 post-normalized main components were selected for back-propagation (BP) neural network training to establish primary AGI grade model of critically ill patients based on the neural network model.

RESULTSA total of 1 132 GIS and 333 AGI were collected from 60 patients. The number (P = 0.0005), percentage of time (P = 0.0004), mean power (P = 0.0088), maximum power (P = 0.0101) and maximum time (P = 0.0025) of GIS wave from the channel located at the stomach were negatively correlated with the AGI grades, while the parameters of GIS wave from the channel located at the intestine had no significant correlation with the AGI grades(all P > 0.05). Three main components were selected after principal component analysis of these five correlated parameters. An AGI grade network model including 9 hide layers, with a fitting degree of 0.981 64 was built by BP artificial neural network based on the analysis of these three main components of GIS. The accuracy rate of the model to predict the AGI grade was 70.83%.

CONCLUSIONThe preliminary model based on GIS in classifying AGI grade is established successfully, which can help predict the classification of AGI grade of critically ill patients.

Abdominal Injuries ; classification ; diagnosis ; Auscultation ; instrumentation ; methods ; statistics & numerical data ; Computer Simulation ; Critical Care ; methods ; Critical Illness ; classification ; Diagnosis, Computer-Assisted ; instrumentation ; methods ; Diagnostic Techniques, Digestive System ; instrumentation ; statistics & numerical data ; Humans ; Models, Biological ; Neural Networks (Computer) ; Predictive Value of Tests

The application of independent component analysis (ICA) to the functional magnetic resonance imaging (fMRI) data can separate many independent sources. But in the processing there are two difficulties: (1) the data of the fMRI is usually on a large scale, so the computing is time-consuming; (2) we cannot avoid the errors for too heavy computational load, this brings many troubles. Thus we think of reducing the data. In this article we used the standard information theoretic methods to estimate the number of the sources and used the principal component analysis (PCA) to reduce the data. By this process, we estimated the number of the sources and reduced the data successfully; Then we applied the ICA algorithm to the reduced fMRI data; this method raised the speed of operation. After application of the new ICA algorithm and another algorithm (FastICA) to the fMRI data, a comparison was made. The results show that the new algorithm can separate the fMRI data fast and effectively and it is superior to the FastICA on the accuracy of estimating the temporal dynamics of activations.
Algorithms ; Humans ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging ; methods ; statistics & numerical data ; Male ; Principal Component Analysis ; Signal Processing, Computer-Assisted ; Software ; Young Adult

The objective of this study was to investigate the mechanical characteristics of implant-abutment interface design in a dental , using nonlinear finite element analysis (FEA) method. This finite element simulation study was applied on three commonly used commercial dental implant systems: model I, the reduced-diameter 3i implant system (West Palm Beach, FL, USA) with a hex and a 12-point double internal hexagonal connection; model II, the Semados implant system (Bego, Bremen, Germany) with combination of a conical (450 taper) and internal hexagonal connection; and model III, the Brinemark implant system (Nobel Biocare, Gothenburg,Sweden) with external hexagonal connection. In simulation, a force of 170 N with 45" oblique to the longitudinal axis of the implant was loaded to the top surface of the abutment. It has been found from the strength and stiffness analysis that the 3i implant system has the lowest maximum von Mises stress, principal stress and displacement while the Br Bnemark implant system has the highest. It was concluded from our preliminary study using nonlinear FEA that the reduced-diameter 3i implant system with a hex and a 12-point double internal hexagonal connection had a better stress distribution, and produced a smaller displacement than the other two implant systems.
Computer Simulation ; Computer-Aided Design ; Dental Implant-Abutment Design ; statistics & numerical data ; Dental Prosthesis Design ; Dental Stress Analysis ; methods ; Finite Element Analysis ; Humans ; Stress, Mechanical