Intelligent Electrocardiogram Analysis in Medicine: Data, Methods, and Applications / 中国医学科学杂志(英文版)

Electrocardiogram (ECG) is a low-cost, simple, fast, and non-invasive test. It can reflect the heart's electrical activity and provide valuable diagnostic clues about the health of the entire body. Therefore, ECG has been widely used in various biomedical applications such as arrhythmia detection, disease-specific detection, mortality prediction, and biometric recognition. In recent years, ECG-related studies have been carried out using a variety of publicly available datasets, with many differences in the datasets used, data preprocessing methods, targeted challenges, and modeling and analysis techniques. Here we systematically summarize and analyze the ECG-based automatic analysis methods and applications. Specifically, we first reviewed 22 commonly used ECG public datasets and provided an overview of data preprocessing processes. Then we described some of the most widely used applications of ECG signals and analyzed the advanced methods involved in these applications. Finally, we elucidated some of the challenges in ECG analysis and provided suggestions for further research.

Design and implementation of a modular pulse wave preprocessing and analysis system based on a new detection algorithm / 生物医学工程学杂志

As one of the standard electrophysiological signals in the human body, the photoplethysmography contains detailed information about the blood microcirculation and has been commonly used in various medical scenarios, where the accurate detection of the pulse waveform and quantification of its morphological characteristics are essential steps. In this paper, a modular pulse wave preprocessing and analysis system is developed based on the principles of design patterns. The system designs each part of the preprocessing and analysis process as independent functional modules to be compatible and reusable. In addition, the detection process of the pulse waveform is improved, and a new waveform detection algorithm composed of screening-checking-deciding is proposed. It is verified that the algorithm has a practical design for each module, high accuracy of waveform recognition and high anti-interference capability. The modular pulse wave preprocessing and analysis software system developed in this paper can meet the individual preprocessing requirements for various pulse wave application studies under different platforms. The proposed novel algorithm with high accuracy also provides a new idea for the pulse wave analysis process.

Research Trends and Future Issues Related to Pre-analysis Data Preprocessing in Large-scale Real-World Data ―With the Goal of Using it in Clinical Research― / 薬剤疫学

In recent years, the utilization of health care databases has been increasing worldwide. It is expected that Real World Data (RWD) will soon be effectively used for clinical research in Japan. On the other hand, database studies that use accumulated existing data such as electronic medical records, Diagnosis Procedure Combinations (DPCs), and health insurance claims, require extremely high loads of data preprocessing before statistical analysis is possible. So far, there is insufficient literature that describes the challenges of RWD preprocessing from an academic point of view. In this review paper, the challenges of database study are classified into three categories：（1）data content,（2）data structure, and（3）large-volume data handling. We then investigated existing preprocessing research and systematically introduced them. Most data preprocessing research targeted the improvement and reliability of the database itself through supplementing data contents required for each clinical research. There is very little research with the primary purpose of solving problems related to data structures and large-volume data processing. As the use of RWD for clinical research increases, the importance of the data preprocessing field will be recognized. In the future, we expect to see more research focused on RWD, which can enable the growth of clinical researches using RWD.

A computed tomography image segmentation algorithm for improving the diagnostic accuracy of rectal cancer based on U-net and residual block / 生物医学工程学杂志

As an important basis for lesion determination and diagnosis, medical image segmentation has become one of the most important and hot research fields in the biomedical field, among which medical image segmentation algorithms based on full convolutional neural network and U-Net neural network have attracted more and more attention by researchers. At present, there are few reports on the application of medical image segmentation algorithms in the diagnosis of rectal cancer, and the accuracy of the segmentation results of rectal cancer is not high. In this paper, a convolutional network model of encoding and decoding combined with image clipping and pre-processing is proposed. On the basis of U-Net, this model replaced the traditional convolution block with the residual block, which effectively avoided the problem of gradient disappearance. In addition, the image enlargement method is also used to improve the generalization ability of the model. The test results on the data set provided by the "Teddy Cup" Data Mining Challenge showed that the residual block-based improved U-Net model proposed in this paper, combined with image clipping and preprocessing, could greatly improve the segmentation accuracy of rectal cancer, and the Dice coefficient obtained reached 0.97 on the verification set.

Detecting anomalous growth of skin lesion using threshold-based segmentation algorithm and Fuzzy K-Nearest Neighbor classifier

Context: Skin cancer is a complex and life-threatening disease caused primarily by genetic instability and accumulation of multiple molecular alternations. Aim: Currently, there is a great interest in the prospects of image processing to provide quantitative information about a skin lesion, that can be relevance for the clinical images and also used as a stand-alone cautioning tool. Setting and Design: To accomplish a powerful approach to recognize skin cancer without performing any unnecessary skin biopsies, this article presents a new hybrid technique for the classification of skin images using Firefly with K-Nearest Neighbor algorithm (FKNN). Materials and Methods: FKNN classifier is used to predict and classify skin cancer along with threshold-based segmentation and ABCD feature extraction. Image preprocessing and feature extraction techniques are mandatory for any image-based applications. Statistical Analysis Used: Initially, it is essential to eliminate the illumination variation and the other unwanted shadow areas present in the skin image, which is done by homomorphic filtering called preprocessing. Results: The comparison of our proposed method with other existing methods and a comprehensive discussion is explored based on the obtained results. Conclusion: The proposed FKNN provides a quantitative information about a skin lesion through hybrid KNN and firefly optimization that helps for recognizing the skin cancer efficiently than other technique with low computational complexity and time

Attenuating the potential hepatotoxicity of Psoraleae Fructus by pre-processing: the alcohol soaking and water rinsing method / 药学学报

Recently, the hepatotoxicity issue regarding to Psoraleae Fructus (PF) has attracted remarkable concerns, which highlights the urgent need to explore the toxicity attenuation method for PF. In this study, we proposed an alcohol soaking and water rinsing method for pre-processing PF based on the record in the classics - "Lei Gong Pao Zhi Lun", aiming to attenuate the potential hepatotoxicity of PF. The optimal pre-processing methods and parameters were investigated by U*12(108) uniform design coupled with 3D-cultured human-derived liver organoids model and high-content imaging. The results showed that there were significant variations among the hepatotoxicity intensities of different pre-processed PF products. Four factors, including the concentration of alcohol, the ratio of material and alcohol in alcohol soaking, the time of alcohol soaking and the times of water rinsing, were found as independent significant factors (all P<0.01). The optimal pre-process parameters were further predicted and verified as follows: the alcohol concentration is 80%, the times of alcohol soaking is 3, the ratio of alcohol and material of alcohol soaking is 3, the time for alcohol soaking is 30 h, the ratio of water and material of water rinsing is 2, the times of water rinsing is 3, the time water rinsing is 12 h and the time of steaming is 5 h. This research demonstrated that the alcohol soaking and water rinsing method can effectively reduce the potential hepatotoxicity of PF. This method provides a reference for reducing the risk of PF liver injury from the perspective of Chinese medicinal materials pre-processing.

A DenseNet-based diagnosis algorithm for automated diagnosis using clinical ECG data / 南方医科大学学报

OBJECTIVE@#To train convolutional networks using multi-lead ECG data and classify new data accurately to provide reliable information for clinical diagnosis.@*METHODS@#The data were pre-processed with a bandpass filter, and signal framing was adopted to adjust the data of different lengths to the same size to facilitate network training and prediction. The dataset was expanded by increasing the sample size to improve the detection rate of abnormal samples. A depth-wise separable convolution structure was used for more specific feature extraction for different channels of twelve-lead ECG data. We trained the two classifiers for each label using the improved DenseNet to classify different labels.@*RESULTS@#The propose model showed an accuracy of 80.13% for distinguishing between normal and abnormal ECG with a sensitivity of 80.38%, a specificity of 79.91% and a F1 score of 79.35%.@*CONCLUSIONS@#The model proposed herein can rapidly and effectively classify the ECG data. The running time of a single dataset on GPU is 33.59 ms, which allows real-time prediction to meet the clinical requirements.

Processing of impedance cardiogram differential for non-invasive cardiac function detection / 生物医学工程学杂志

The precise recognition of feature points of impedance cardiogram (ICG) is the precondition of calculating hemodynamic parameters based on thoracic bioimpedance. To improve the accuracy of detecting feature points of ICG signals, a new method was proposed to de-noise ICG signal based on the adaptive ensemble empirical mode decomposition and wavelet threshold firstly, and then on the basis of adaptive ensemble empirical mode decomposition, we combined difference and adaptive segmentation to detect the feature points, A, B, C and X, in ICG signal. We selected randomly 30 ICG signals in different forms from diverse cardiac patients to examine the accuracy of the proposed approach and the accuracy rate of the proposed algorithm is 99.72%. The improved accuracy rate of feature detection can help to get more accurate cardiac hemodynamic parameters on the basis of thoracic bioimpedance.

Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review / 基因组蛋白质组与生物信息学报·英文版

Various methods and specialized software programs are available for processing two-dimensional gel electrophoresis (2-DGE) images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and horizontal streaking, fuzzy spots, and background noise, which greatly complicate computational analysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images: Gaussian, Rayleigh, and exponential, with signal-to-noise ratios (SNRs) ranging 8-20 decibels (dB). We compared the performance of wavelet, contourlet, total variation (TV), and wavelet-total variation (WTTV) techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sensitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10-20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best performance with any level of Gaussian noise and low levels (20-14 dB) of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image.

Effects of three aqueous extraction preprocessing methods on total coumarins extract of Angelicae dahuricae Radix / 中成药

AIM To investigate the effects of aqueous extraction at normal temperature,40 ℃,and water boiling on total coumarins extract of Angelicae dahuricae Radix.METHODS For the extracts Ⅰ-Ⅳ obtained by ethanol reflux extraction and three aqueous extraction preprocessing methods,respectively,UV and HPLC were adopted in the content determination of total coumarins and imperatorin,then the powder properties and dissolution rates were compared.RESULTS The contents of total coumarins in four extracts were 3.98％,6.03％,6.81％ and 4.46％,while those of imperatorin were 0.633％,0.540％,0.465％ and 0.155％,respectively.The angles of repose were 48.455°,42.587°,42.689° and 42.024° with the bulk densities of 0.214,0.324,0.316 and 0.354 g/cm3,respectively.Within 100 min,extract Ⅰ demonstrated higher moisture adsorption rate and equilibrium moisture absorption content than the other three extracts.The accumulative dissolution rates of various extracts were much higher than that of medicinal material fine powder within 120 min.CONCLUSION All the three aqueous extraction preprocessing methods can obviously improve the powder properties of total coumarins extract of A.dahuricae Radix and increase the dissolution rate of medicinal material fine powder.

Combination of noise removal and contrast enhancement methods for the preprocessing of mammogram images - towards the detection of breast cancer / Combinação de métodos de remoção de ruído e aperfeiçoamento de contraste para o pré-processamento de imagens de mamografias - rumo à detecção do câncer de mama

Breast cancer is a major killer disease for women and men. It can be treated and controlled only if it is detected at its earlier stage. Early detection can be achieved by the help of Computer Aided Detection (CAD) methods. From the detailed study on previous researches, it is found that, there is no system producing 100% accuracy because of one or more reasons. Absence of effective preprocessing is the discussed reason that obstructs the detection accuracy of CAD method. Noise removal and contrast enhancement are the two types of preprocessing. There is no system performs both the preprocessing on mammogram image. This work is an attempt to develop an enhanced preprocessing method for CAD of breast cancer by incorporating suitable noise reduction and contrast enhancement methods in the conventional CAD system. Among the available noise reduction techniques, Fast Discrete Curvelet Transform (FDCT) based UnequiSpaced Fast Fourier Transform (USFFT) has been utilized and the Modified Local Range Modification (MLRM) technique has been utilized for contrast enhancement. Contrast enhancement after noise reduction double enhances the mammogram image and the proposed methods MSE value for the mammogram image mdb072 has been 1.44% reduced when comparing to the LRM method. Reduction in MSE increases the PSNR to 0.16%. Many mammogram images have been tested and the result shows that, increase in contrast, decrease in mean square error and increase in peak signal to noise ratio when comparing to existing methods.

Introdução: O câncer de mama é uma grande doença mortal para mulheres e homens. Ele só pode ser tratado e controlado se for detectado em sua fase inicial. A detecção precoce pode ser alcançada com a ajuda de métodos de detecção assistida por computador (CAD). A partir do estudo detalhado sobre pesquisas anteriores, verifica-se que, não há um sistema com 100% de precisão por causa de uma ou mais razões. A ausência de pré-processamento efetivo é o motivo discutido que obstrui a precisão de detecção do método CAD. A remoção de ruído e o aprimoramento do contraste são os dois tipos de pré-processamento. Não existe um sistema que realize ambos os pré-processamentos na imagem da mamografia. Objetivo: Este trabalho é uma tentativa de desenvolver um método de pré-processamento aprimorado para CAD de câncer de mama, incorporando métodos adequados de redução de ruído e aprimoramento de contraste no sistema de CAD convencional. Métodos: Entre as técnicas de redução de ruído disponíveis, a transformada de curva discreta rápida (FDCT) baseada na transformada rápida de Fourier desigualmente espaçada (USFFT) foi utilizada e a técnica de modificação de faixa local modificada (MLRM) foi utilizada para aprimoramento de contraste. Resultados: o aprimoramento do contraste após a redução do ruído melhora o dobro da imagem da mamografia e os métodos propostos para o valor de MSE para a imagem da mamografia mdb072 foram reduzidas em 1,44% quando comparados ao método LRM. A redução de MSE aumenta o PSNR para 0,16%. Conclusão: muitas imagens de mamografia foram testadas e o resultado mostra que, aumento no contraste, diminuição do erro quadrático médio e aumento da relação pico do sinal/ruído quando comparado aos métodos existentes.

The Overview of Ontology Alignment techniques and Their Applications to Traditinoal Chinese Medicine (TCM) / 世界科学技术-中医药现代化

Ontology alignment technology is a knowledge engineering method to realize the concept and relationship integration of different ontologies.In view of the same scope of ontology,such as disease ontology,developed by researchers from a number of different areas or institutions of independent research and development,there is a big difference between the term expression and the concept of the relationship.Thus,how to achieve the integration of multi-source ontology through alignment processing has been recognized as a significant methodological problem.In this paper,the concept,technology,method and corresponding tool of ontology alignment were expounded at full length.The technique of ontology alignment based on linguistic features and structural features was emphasized.Combined with the two international disease ontology:Disease Ontology and Orphanet,the experiment and analysis of the technique of ontology alignment were carried out and detailed the application of alignment technology.Furthermore,for the existing multi-source problems on TCM ontology database,the necessity and application of ontology alignment were discussed.

Study on Pre-processing Methods of Clinical Data from TCM Individual Treatment of Insomnia Based on Syndrome Differentiation / 中国中医药信息杂志

Objective To explore suitable pre-processing methods for the TCM clinical data based on prospective study on insomnia treated by syndrome differentiation. Methods Based on the TCM shared clinical and research information platform and by using man-machine combination method, data cleaning rules, physician review, rule revision, procedural import and batch processing were used to conduct pre-processing for data in prospective study on insomniac treated by syndrome differentiation of 8 TCM doctors. Results Totally 27534 rules for symptoms data of individual treatment of insomnia were made and 1036 rules for diagnostic data, 842 rules for therapeutic ways, 540 rules for formula data, 3785 rules for data of Chinese materia medica. Conclusion Different kinds of terminology concepts were normalized at different levels, at the same time, characteristics of individualized treatment based on syndrome differentiation were reserved. Appropriate pre-processing methods can be used in the reaserch of individualization and standardization of TCM syndrome differentiation clinical data and can provide support for data mining.

Clinical significance of pre-processing of sputum specimens / 国际检验医学杂志

Objective To investigate the influence of sputum specimens pre-processing on the detection result and its clinical sig-nificance .Methods The sputum samples of 124 inpatients in this hospital from February 2016 to April 2016 were selected .The sputum color ,character ,Gram staining microcopic examinationof sputum smear were observed by adopting the naked-eye observa-tion .Its influence on the sputum specimen isolation results was analyzed .Results Among 124 sputum specimens ,90 cases were qualified ,while 34cases were unqualified ;the qualification rate of colorlesssputum specimens was 30% ,which was lower than 94 .7% of yellow sputum specimens ,100% of rusty sputum specimens ,100% of red sputum specimens and 87 .5% of white sputum specimens ;the qualification rate of frothy or watery sputum specimens was 22 .2% ,which was lower than that of other character sputum specimens ,such as purulent sputum specimens (96 .2% ) ,bloody sputum specimens (100% )and mucous sputum specimens (83 .3% );the cultured results of 34 unqualified specimens were the oral and throat normal flora ,which all had the contaminating bacterial growth ;among 90 qualified specimens ,58 specimens showed pure culture or advantage growth ,and 32 specimens showed contaminating bacterial growth .Conclusion The pre-processing of sputum specimens is an efficient solution for improving the accu-racy of sputum specimens detection results ,and has the important clinical significance .

Investigation and improvement of the problems which are caused by pretreating reused medical instruments after usage / 中国实用护理杂志

Objective To discuss the reason of the problem, which are caused by pretreating reused medical instruments after usage in each hospital clinical departments;ensure the washing quality for the reused medical instruments and prolonging the working life of them. Methods The execution rate, washing quality, damage of which pretreating reused medical instruments in clinical departments were counted The Clinic of Infection, Nursing Department and Central Sterile Supply Department observed and adopted questionnaire for information, and then formulated targeted guidance and improvement according to the information. Results The execution rate of pretreating reused medical instrument after usage reached from 64.6% to 99.4%, the qualified rate of instrument washing had improved from 93.0% to 99.7%,the damage rate of instruments had decreased from 1.84% to 0.74%,and there were significant differences(χ2=9 413.8,38 160.6,2 820.2,all P<0.05). Conclusions Pretreating reused medical instrument after usage correctly and timely,can not only ensure the washing quality for the medical instruments, but also prolong the working life of them. It ensures the application value of the medical instruments.

Ajuste de modelos e difusividade efetiva na secagem de folhas de Azadirachta indica A. Juss / Ajuste de los modelos y la difusividad efectiva en el secado de las hojas de Azadirachta indica A. Juss / Adjustment of models and effective diffusivity in the drying of Azadirachta indica A. Juss. leaves

Introdução: a espécie Azadirachta indica A. Juss. conhecida como neem indiano, possui ampla utilização nas áreas da medicina, agropecuária e cosmética, proporcionada particularmente pelas folhas desidratadas. Devido à importância da espécie, tem-se a necessidade de conhecimentos específicos no seu pré-processamento. Objetivo: determinar a curva de secagem, ajustar modelos não lineares aos dados, estimar o coeficiente de difusividade efetiva e a energia de ativação durante a secagem das folhas de A. indica, em diferentes temperaturas. Métodos: as folhas da referida espécie foram submetidas à secagem em diferentes temperaturas com quatro repetições em secador de camada fixa. Utilizaram-se doze modelos para testar o comportamento da cinética de secagem, e seleciono-os que melhor desempenharam respostas funcionais considerando a magnitude do coeficiente de determinação, qui-quadrado, erro médio relativo e desvio padrão. Ainda, ajustou os dados, ao modelo matemático da difusão líquida com a solução analítica para a placa plana infinita, com aproximação de oito termos. Os gráficos foram elaborados pelo Sigma Plot. Resultados: evidenciou ajuste satisfatório para os modelos de Verma, Newton, Midilli, Logarítmico e Aproximação da Difusão, porém selecionou-se o modelo de Newton por apresentar maior simplicidade de aplicação. Constatou-se que com aumento da temperatura, ocorre um decréscimo no tempo de secagem e aumento na intensidade do fenômeno de transporte de água. Conclusões: a energia de ativação foi de 27,77 kJ mol-1. O modelo de Newton pode ser utilizado para descrever a cinética de secagem das folhas de A. indica. A energia de ativação se mostrou dentro do intervalo indicado para produtos agrícolas(Introdução: a espécie Azadirachta indica A. Juss. conhecida como neem indiano, possui ampla utilização nas áreas da medicina, agropecuária e cosmética, proporcionada particularmente pelas folhas desidratadas. Devido à importância da espécie, tem-se a necessidade de conhecimentos específicos no seu pré-processamento. Objetivo: determinar a curva de secagem, ajustar modelos não lineares aos dados, estimar o coeficiente de difusividade efetiva e a energia de ativação durante a secagem das folhas de A. indica, em diferentes temperaturas. Métodos: as folhas da referida espécie foram submetidas à secagem em diferentes temperaturas com quatro repetições em secador de camada fixa. Utilizaram-se doze modelos para testar o comportamento da cinética de secagem, e seleciono-os que melhor desempenharam respostas funcionais considerando a magnitude do coeficiente de determinação, qui-quadrado, erro médio relativo e desvio padrão. Ainda, ajustou os dados, ao modelo matemático da difusão líquida com a solução analítica para a placa plana infinita, com aproximação de oito termos. Os gráficos foram elaborados pelo Sigma Plot. Resultados: evidenciou ajuste satisfatório para os modelos de Verma, Newton, Midilli, Logarítmico e Aproximação da Difusão, porém selecionou-se o modelo de Newton por apresentar maior simplicidade de aplicação. Constatou-se que com aumento da temperatura, ocorre um decréscimo no tempo de secagem e aumento na intensidade do fenômeno de transporte de água. Conclusões: a energia de ativação foi de 27,77 kJ mol-1. O modelo de Newton pode ser utilizado para descrever a cinética de secagem das folhas de A. indica. A energia de ativação se mostrou dentro do intervalo indicado para produtos agrícolas(AU)

Introducción: la especie Azadirachta indica A. Juss. conocida como indiano, posee amplia utilización en las áreas de la medicina, agropecuaria y cosmética, proporcionada particularmente por las hojas deshidratadas. Debido a la importancia de la especie, existe la necesidad de un conocimento específico en su pre-procesamiento. Objetivo: determinar la curva del secado, ajustar los modelos no lineales con los datos y estimar el coeficiente de difusividad efectiva y de la energia de activación durante el secado de las hojas de A. indica, a diferentes temperaturas. Métodos: las hojas de dicha especie, fueron sometidas a un secado a diferentes temperaturas con cuatro repeticiones en el secador de capa fija. Se utilizaron doce modelos para probar el comportamiento de la cinética de secado, y se seleccionaron según los que mejor desempeñaron respuestas funcionales, teniendo en cuenta la magnitud del coeficiente de determinación, chi-cuadrado, error medio relativo y la desviación típica. Además, se ajustaron los datos al modelo matemático de difusión líquida con la solución analítica para la placa plana infinita, con la aproximación de 8 terminos. Los gráficos fueron confeccionados por Sigma Plot. Resultados: se mostró un ajuste satisfactório para los modelos de Verma, Newton, Midilli, Logarítmico y la aproximación de difusión, sin embargo se selecionó el modelo de Newton, por presentar mayor simplicidad de aplicación. Se constató que con el aumento de la temperatura ocurre una disminución en el tiempo de secado y aumento en la intensidad del fenomeno de transporte del agua. Conclusiones: la energia de activación fue de 27,77 kJ mol-1. El modelo de Newton puede ser utilizado para describir la cinética de secado de las hojas de A. indica. La energía de activación se mostró dentro del alcance indicado para productos agrícolas(AU)

Introduction: The species Azadirachta indica A. Juss, commonly known as Indian neen, is broadly used in medicine, agriculture and the cosmetic industry, mainly in the form of dehydrated leaves. Due to the importance of this species, specific knowledge is required for its preprocessing. Objective: Determine the drying curve, adjust non-linear models to the data, and estimate the effective diffusivity and activation energy coefficient during the drying of A. indica leaves at different temperatures. Methods: Leaves from the study species were dried at different temperatures with four replications in the fixed layer dryer. Twelve models were used to test the behavior of the drying kinetics. These were selected from among those providing better functional responses, bearing in mind the magnitude of the determination coefficient, chi-square, relative mean error and typical deviation. Additionally, data were adjusted to the liquid diffusion mathematical model with the analytical solution for the infinite plane plate with an approximation of 8 terms. The charts were developed by Sigma Plot. Results: A satisfactory adjustment was achieved for the models Verma, Newton, Midilli, logarithmic, and diffusion approximation, but the Newton model was chosen, due to the simplicity of its application. It was found that as temperature increases, there is a decrease in drying time and an increase in water transport intensity. Conclusions: Activation energy was 27.77 kJ mol-1. The Newton model may be used to describe the drying kinetics of A. indica leaves. Activation energy was within the scope established for agricultural products(AU)

Analysis and application of TCM data preprocessing method based on Apriori algorithm / 医疗卫生装备

To present a data processing method of traditional Chinese medicine based on Apriori algorithm to improve the efficiency of data mining and ensure the accuracy of the knowledge or conclusion in the data mining. The importance of data preprocessing in data mining was analyzed, along with the characteristics of TCM data and the requirements of Apriori algorithm for mining data. Some new functions were formed with considerations on the exam-ples. The data preprocessing was explored from the aspects of terminology standardization, eliminating unqualified data, structured prescription data, data sorting and etc. The new functions were simple and easy to operate, and the preprocessed data made the efficiency of TCM data mining enhanced greatly. The preprocessing method based on Apriori algorithm for TCM data facilities the TCM data mining.

Metodología de pre-procesamiento de datos adquiridos por MALDI-MSI en muestras de tejidos / Pre-processing methodology of acquired data by MALDI-MSI in tissue samples

En la última década, la Imagenología por Espectrometría de Masas MALDI (MALDI-MSI) ha demostrado su potencial en el campo de la proteómica. Debido a la alta dimensionalidad de los conjuntos de datos obtenidos en los experimentos de MADI-MSI y las variabilidades inherentes al proceso de adquisición, presentes en los mismos, se hace necesario llevar a cabo una etapa de pre-procesamiento, que reduzca estas distorsiones. La presente investigación propone una metodología de procesamiento de datos de MALDI-MSI sustentada en un conjunto de aplicaciones desarrolladas en MatLab, la Biblioteca Qt4, así como la herramienta de visualización DataCube Explorer. Entre los resultados se pueden destacar la obtención de cambios en las intensidades de los píxeles de las imágenes reconstruidas después de la introducción de ruido, así como el incremento de la Relación Señal-Ruido después de someter los espectros a los métodos de filtrado de Kaiser, Savitzky-Golay y Promedio deslizante, destacándose Kaiser sobre los demás, lo que puede traducirse como una disminución de los niveles de distorsión en los espectros de cada pixel. Se realizó la reconstrucción satisfactoria de la imagen patrón y su visualización con la herramienta DataCube Explorer(AU)

At last decade, MALDI Mass Spectrometry Imaging (MALDI-MSI) has demostrated being a powerful tool in proteomics field. Because of high dimensionality of the acquired datasets in MALDI-MSI experiments and the inherent variabilities to the acquisition process, present in them, it´s necessary carry out a pre-processing stage, which reduces these distortions. This paper proposes a processing methodology of data MALDI-MSI supported in applications developed in MATLAB, Qt4 Library, as well as the visualization tool Datacube Explorer. Among the results obtained, it can be highlighted the changes in the intensities of the pixels of the reconstructed images after introducing noise, as well as the increasing of Signal-Noise Ratio after applying the denoising methods Kaiser, Savitzky-Golay and "sliding average", highlighting Kaiser over the other techniques, which can be interpreted as a decreasing of the distortion levels in each pixel´s spectrum. The reconstruction of example image and its visualization with Datacube Explorer tool were satisfactory(AU)

A Quantitative Analysis for Pre-processing Algorithm of Aberration Chromosome Observation / 대한의료정보학회지

The task of chromosome analysis is the classification of human chromosomes. The feature parameter of chromosome is very important information for chromosome analysis. The special preprocessing algorithm is required to extracting them. In this paper, we performed quantitative analysis for preprocessing algorithm of observation of chromosomal aberrations. Two algorithms is used MAT and reconstruction. The morphological feature parameters were centromeric index(C.I.), relative length ratio(R.L.), relative area ratio(R.A.) and chromosome length(C.L.), and the density and width profiles. The reconstruction of chromosome images by this reconstruction algorithm was appeared as effective algorithms to observe and extract chromosome parameter.

A Quantitative Analysis for Pre-processing Algorithm of Aberration Chromosome Observation / 대한의료정보학회지

The task of chromosome analysis is the classification of human chromosomes. The feature parameter of chromosome is very important information for chromosome analysis. The special preprocessing algorithm is required to extracting them. In this paper, we performed quantitative analysis for preprocessing algorithm of observation of chromosomal aberrations. Two algorithms is used MAT and reconstruction. The morphological feature parameters were centromeric index(C.I.), relative length ratio(R.L.), relative area ratio(R.A.) and chromosome length(C.L.), and the density and width profiles. The reconstruction of chromosome images by this reconstruction algorithm was appeared as effective algorithms to observe and extract chromosome parameter.