Prediction of concentration immediately dangerous to life or health of benzene and its derivatives based on quantitative structure-activity relationship / 环境与职业医学

Background With the increasing exposure to hazardous chemicals in the workplace and frequency of occupational injuries and occupational safety accidents, the acquisition of occupational exposure limits of hazardous chemicals is imminent. Objective To obtain more unknown immediately dangerous to life or health (IDLH) concentrations of hazardous chemicals in the workplace by exploring the application of quantitative structure-activity relationship (QSAR) prediction method to IDLH concentrations, and to provide a theoretical basis and technical support for the assessment and prevention of occupational injuries. Methods QSAR was used to correlate the IDLH values of 50 benzene and its derivatives with the molecular structures of target compounds. Firstly, affinity propagation algorithm was applied to cluster sample sets. Secondly, Dragon 2.1 software was used to calculate and pre-screen 537 molecular descriptors. Thirdly, the genetic algorithm was used to select six characteristic molecular descriptors as dependent variables and to construct a multiple linear regression model (MLR) and two nonlinear models using support vector machine (SVM) and artificial neural network (ANN) respectively. Finally, model performance was evaluated by internal and external validation and Williams diagram was drawn to determine the scopes of selected models. Results The ANN model results showed that \begin{document}$ {R}_{\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{i}\mathrm{n}}

Research on multi-Atlas segmentation based on feature clustering / 中华放射肿瘤学杂志

Objective:To study the improvement of normal tissue region of interest (ROI) segmentation based on clustering-based multi-Atlas segmentation method, thereby achieving better delineation of organs at risk.Methods:CT images of 100 patients with cervical cancer who had completed treatment in Zhejiang Cancer Hospital during 2019-2020 were selected as the Atlas database. According to the volume characteristic parameters of the organs at risk (bladder, rectum and outer contour), the Atlas database was divided into several subsets by k-means clustering algorithm. The image to be segmented was matched to the corresponding Atlas library for multi-Atlas segmentation. The dice similarity coefficient (DSC) was used to evaluate the segmentation results.Results:Using 30 patients as the test set, the sub-Atlas generated by different clustering methods were compared for the improvement of image segmentation results. Compared with general multi-Atlas segmentation methods, clustering-based multi-Atlas segmentation method significantly improve the segmentation accuracy for the bladder (DSC=0.83±0.09 vs. 0.69±0.15, P<0.001) and the rectum (0.7±0.07 vs. 0.56±0.16, P<0.001), but no statistical significance was observed for left and right femoral head (0.92±0.04, 0.91±0.02) and bone marrow (0.91±0.06). The average segmentation time of clustering-based multi-Atlas segmentation method was shorter than that of the general multi-Atlas segmentation method (2.7 min vs. 6.3 min). Conclusion:The clustering-based multi-Atlas segmentation method can not only reduce the number of Atlas images registered with the image to be segmented, but also can be expected to improve the segmentation effect and obtain higher accuracy.

Study on medication regularity of traditional Chinese medicine in treatment of COVID-19 based on data mining / 中国中药杂志

The coronavirus disease 2019(COVID-19) is developing rapidly and posing great threat to public health. There is no specific medicine available for treating the disease. Luckily, traditional Chinese medicine has played a positive role in the fighting against COVID-19. In this paper, We collected and sorted the prescriptions of modern Chinese medicine for COVID-19 released by national government, different provinces, autonomous regions and municipalities, as well as online databases, such as CNKI, WanFang medical network, and VIP database. These prescriptions were combined with the inheritance of traditional Chinese medicine auxiliary V2.5, and the complex system entropy clustering method was used to determine the association rules and frequency of single drug and drug combination in the prescription. In the end, 96 effective prescriptions were included. Among them, the four properties were mainly concentrated in temperature, cold and level, the five tastes were mainly concentrated in bitter, hot and sweet, and the meridians were mainly concentrated in lung, stomach and spleen. The high-frequency drugs were Glycyrrhizae Radix et Rhizoma, Armeniacae Semen Amarum, Gypsum Fibrosum, etc., and the high-frequency combinations are Gypsum Fibrosum-Armeniacae Semen Amarum, Gypsum Fibrosum-Glycyrrhizae Radix et Rhizoma, Armeniacae Semen Amarum-Glycyrrhizae Radix et Rhizoma, the core combinations are Lepidii Semen-Armeniacae Semen Amarum-Gypsum Fibrosum, Pogostemonis Herba-Zingiberis Rhizoma Recens-Magnoliae Officinalis Cortex, Ophiopogonis Radix-Armeniacae Semen Amarum-Scutellariae Radix and so on. Form new prescriptions Lepidii Semen, Armeniacae Semen Amarum, Gypsum Fibrosum, Pogostemonis Herba, Zingiberis Rhizoma Recens, Magnoliae Officinalis Cortex. Ophiopogonis Radix, Armeniacae Semen Amarum, Scutellariae Radix, Schisandrae Sphenantherae Fructus, Panacis Quinquefolii Radix. From the medicinal properties to high-frequency drugs and new prescriptions, it could be seen that the overall treatment of COVID-19 by traditional Chinese medicine was to strengthen body resistance, eliminate pathogenic factors, and give attention to Qi and Yin.

Medication rules of Professor Zhang Bing in treatment of skin itching based on data mining / 中国中药杂志

Skin itching is a subjective sensation that causes the desire to scratch. It is one of the most common clinical symptoms at department of dermatology, even the only complaint of dermatological patients, which seriously affects the quality life of patients. Therefore, based on the software of traditional Chinese medicine inheritance auxiliary platform, association rules and complex system entropy clustering were adopted to collect and analyze Zhang Bing's prescriptions for skin itching, and get the drug use frequency and the relationship between drugs. Based on that, we could conclude the experience for skin itching. A total of 147 prescriptions were collected, 20 drugs with a frequency of 34 or more and 20 high-frequency drug combinations were analyzed, and 14 core combinations and 7 new prescriptions were excavated. The high-frequency drugs included Kochiae Fructus, Dictamni Cortex, Mori Cortex. The high-frequency drug combinations included "Kochiae Fructus-Dictamni Cortex" "Angelicae Dahuricae Radix-Chuanxiong Rhizoma" "Paeoniae Radix Rubra-Paeoniae Radix Alba", and the core combinations included "Schizonepetae Herba-Saposhnikoviae Radix-Cinnamomi Ramulus" "Arctii Fructus-Cicadae Periostracum-Houttuyniae Herba" "Ghrysanthemi Indici Flos-Kochiae Fructus-Dictamni Cortex", and new formulations include "Schizonepetae Herba, Saposhnikoviae Radix, Cinnamomi Ramulus, Clematidis Radix et Rhizoma, Tribuli Fructus, Dictamni Cortex", "Phellodendri Chinensis Coritex, Lonicerae Japonicae Flos, Atractylodis Rhizoma, Ghrysanthemi Indici Flos, Kochiae Fructus, Dictamni Cortex" "Arctii Fructus, Cicadae Periostracum, Houttuyniae Herba, Trichosanthis Fructus". The result of this research shows that Professor Zhang Bing's experience in the treatment of skin itching is mainly to dispelling wind and arresting itching, clearing heat and drying dampness.

Research on Traditional Chinese Medicine Professor Niu Jianzhao's Medication Rule in Prescriptions with Climacteric Syndrome Based on Data Mining / 世界科学技术-中医药现代化

This study was aimed to explore traditional Chinese medicine (TCM) professor Niu Jianzhao's medication rule in prescription with climacteric syndrome.Prescriptions treating climacteric syndrome that built by professor Niu were collected to build a database based on TCM Inheritance Assist System.The method of association rules with apriori algorithm was used to achieve frequency of single medicine,nature,taste and channel tropism of herbs,frequency of drug combination,association rules between herbs and core herb combinations.The data mining results showed 22 types of herbs used with high frequency,28 pairs of herb combination with most frequency,20 groups of herb association rules with the confidence of more than 0.95,52 herb pairs with high association,32 groups of three herbs as the core combinations,and 7 new prescriptions.It was concluded that in professor Niu Jianzhao's treatment of climacteric syndrome,the drugs were commonly used to invigorate the kidney,liver and spleen,and in combination with promoting blood circulation and calming the nerves.The medicinal properties of used herbs were even,warm or slightly cold.The tastes of used herbs were sweet,bitter and spicy.The channel tropisms of used herbs were the liver,kidney and lung meridian.This study highlighted data mining as an important tool for expedited analysis of TCM professor Niu Jianzhao's medication rules in prescriptions with climacteric syndrome.

Research on medication rules of urticaria treatment based on data mining / 国际中医中药杂志

Objective A traditional Chinese medicine (TCM) inheritance assist system software was used to analyze the medication experiences of treating urticaria.Methods Literatures in three TCM medical books about the treatment of urticaria were collected and analyzed in terms of the utilizing frequency and association rules between different medicines. Data mining research methods such as Apriori algorithm, complex system entropy cluster and unsupervised hierarchical cluster were used in the research.Results Based on 138 screened prescriptions, the study confirmed that the frequency of using Radix sileriswas was highest, and 20 drugs elected in 218 prescription drugs were used more than 20 times. According to the utilizing frequency order of pharmaceutical compositions from high to low, association rules between drugs ranked in the top four were‘ Radix sileris- Cicada slough’, ‘Radix sileris- Schizonepeta’, ‘Radix sileris- Paeonia’, and ‘Schizonepeta- Cicadaslough’. Meanwhile, 30 pharmaceutical drug combinations and 14 new prescriptions were found. Conclusion The research, based on TCM inheritance assist system software platform and data mining method on medication rules of urticaria treatment prescriptions, is instructive in the clinical treatment of urticaria and also provide useful reference for the development of the new drug on urticaria.

Analysis on the Medication Rules of National TCM Masters for the Treatment of Phymatosis Based on Data Mining / 中国中医药信息杂志

Objective To explore the medication rules of national TCM masters’ treatment for phymatosis. Methods The prescriptions for phymatosis of national TCM masters were collected to build a database. The methods of association rules with apriori algorithm and complex system entropy cluster were used to achieve frequency of individual herbs, frequency of medicine combinations, association rules of herbs and core medicine combinations. Results In the prescriptions for phymatosis, Chinese medicinal herbs with the highest frequency were Astragali Radix, Pinelliae Rhizoma, Poria, Herba Oldenlandiae, Rehmanniae Radix Exsiccata, and so on. Medicine combinations with the highest frequencywere Atractylodis Macrocephalae Rhizoma-Poria, Citri Reticulatae Pericarpium-Poria, Atractylodis Macrocephalae Rhizoma-Codonopsis Radix, and Poria-Codonopsis Radix. The medicine association rules of confidence coefficient 1 were Sparganii Rhizoma→Curcumae Rhizoma, and Moutan Cortex, Persicae Semen→Paeoniae Radix Rubra. The new prescriptions composited by “Curcumae Rhizoma, Sparganii Rhizoma, Manis Squama, Prunella Spica, Dipsacus Asperoides”, or “Paridis Rhizoma, Adenophorae Radix, Gleditsiae Spina, Sargassum, Laminariae Thallus”. Conclusions Chinese medicinal herbs used in the prescriptions of national TCM masters for the treatment of phymatosis were often with the actions of invigorating the spleen and benefiting qi, clearing away heat and toxic material, and promoting blood circulation to remove blood stasis, which were complied with the medication rule of treating both the incidental and fundamental aspects in TCM.

Analysis on the principle of Yang Boliang for the treatment for dysentery based on apriori and clustering algorithm / 国际中医中药杂志

Objective To analyze the experience of Yang Boliang for the treatment of dysentery. Methods The prescriptions for dysentery that used by Yang Boliang were collected to build a database, and analyzed by the unsupervised data mining methods, such as apriori algorithm, entropy Clustering complex systems. Results Based on the analysis of 35 prescriptions, the most frequently used drug, the core drug combinations and the new prescriptions were mined from the database. The most frequently used drugs were tuckahoe, rhizoma pinellinae praeparata, and roasted radix puerariae. The core drug combinations were“tuckahoe- radix scutellariae-moutan bark”, “plantago seed-rhizoma pinellinae praeparata-maticated leaven”, and “charred radix aucklandiae-charred radix etrhizoma rhei-waterlily leaf”, etc. The new prescriptions were such as “plantago seed-rhizoma pinellinae praeparata-maticated leaven-charred radix rehmanniae recen-processed rhizoma Cyperi”. Conclusion Yang Boliang was well experienced in treating dysentery by using the drugs with clearing heat, and drying dampness, and clearing dampness by promoting diuresis.

Thalamus segmentation based on resting-state functional magnetic resonance imaging / 国际生物医学工程杂志

Objective To obtain an accurate and effective method for thalamus segmentation based on resting-state functional magnetic resonance imaging (fMRI).Methods Based on the fact that resting-state fMRI technique examined spatial synchronization of spontaneous fluctuations in blood oxygen level-dependent (BOLD) signals indirectly reflect the neuronal and synaptic activity,the in-thalamus BOLD signal correlations were calculated,and then the k-means clustering algorithm was applied to obtain functional connectivity-based thalamus segmentation.Results The thalamus was divided into seven regions.Voxels within the same region were highly correlated with each other.The segmentation result was similar to that divided by functional connectivity between thalamus and the cerebral cortex.Conclusions Resting-state fMRI could provide not only the functional connectivity network between cortical and subcortical brain regions,but also the functional characteristics of thalamus.Segmentation algorithm using only internal information of thalamus shows lower computational complexity and higher processing speed than that based on the functional connectivity between thalamus and the cerebral cortex.

Analysis on the principle of Yang Boliang for the treatment of exogenous diseases based on apriori and clustering algorithm / 国际中医中药杂志

Objective To analyze the experience of Yang Boliang for the treatment of exogenous diseases. Methods The prescriptions for exogenous diseases that used by Yang Boliang were collected to build a database, and analyzed by the unsupervised data mining methods, such as apriori algorithm, entropy Clustering complex systems. Results The most frequently used drugs were tuckahoe, stir-baked fructus gardenia, rhizoma pinellinae praeparata, radix curcumae, radix scutellariae, tetrapanacis medulla, poria cocos, caulis bambusae in taenian, lobster sauce, bitter almond, poria with hostood, fructus forsythiae and so on. The core drug combinations were “fructus forsythia- burdock- lobster sauce”, “semen sojae germinatum- radix liquiritiae-talcum- poria with hostood”, “bitter almond- balloon flower- mulberry leaf”, and so on. Conclusion Yang Boliang treated exogenous diseases by using the drugs with relieving superficies by cooling, dispelling dampness and promoting dieresis.

Analysis on Menghe physician Ma Peizhi's medication rule in prescriptions for impediment syndrome based on knowledge-discovery in database / 国际中医中药杂志

Objeetive To analyze the experiences for impediment syndrome of Ma Peizhi of Menghe Medical Genre by using traditional Chinese medicine (TCM) inheritance support system.Method The prescriptions for impediment syndrome of Ma Peizhi were collected and inputted to TCM inheritance support system,from which we can get the frequency of drug usage and the relationship between drugs based on the association rules and clustering algorithm.Results In the 61 prescriptions,the drugs that used most frequently were Chinese Angelica,Largeleaf Gentian Root,and Twotoothed Aehyranthes Root,and the drug combinations that used most frequently were Largeleaf Gentian Root-Chinese Angelica,Chinese Angelica-Largeleaf Gentian Root,Chinese Angelica-Mulberry Twig.And there were also 26 core combinations and 13 new prescriptions mined from the database.Conclusion Ma Peizhi of Menghe Medical Genre was well experienced impediment syndrome by dispelling wind and removing dampness,and promoting blood circulation by removing blood stasis,from which we can make a conclusion that TCM inheritance support system can be used to analyze the doctors' clinical experiences.

Analysis on Medication Rules of National Medical Masters for Treatment of Hepatopathy ;Based on Data Mining / 中国中医药信息杂志

Objective To investigate the medication rules for the treatment of hepatopathy by national medical masters. Methods The prescriptions for hepatopathy were collected to build a database based on Traditional Chinese Medicine (TCM) inheritance assist system. After analyzed by the data mining, such as apriori algorithm and complex system entropy cluster, the frequency of single medicine and drug combinations that used in prescriptions, and the association rules among drugs were obtained. Results The most frequently used drugs were Herba Artemisiae Capillaris, Tuckahoe, Radix Salviae Miltiorrhizae, Rhizoma Atractylodis Macrocephalae, and Radix Bupleuri, et al. The most frequently used drug combinations were “Radix Salviae Miltiorrhizae, Tuckahoe”, “Rhizoma Atractylodis Macrocephalae, Tuckahoe”, and “Radix Salviae Miltiorrhizae, Herba Artemisiae Capillaris”, et al. And when the confidence of drug association rules was 1, the drug combinations were“Radix et Rhizoma Rhei, Giant Knotweed→Herba Artemisiae Capillaris”,“Radix et Rhizoma Rhei, Radix curcumae→Herba Artemisiae Capillaris”, “Giant Knotweed, Gardenia→Herba Artemisiae Capillaris” and so on. Conclusion The medicines were often with the actions of clearing heat, removing dampness, regulating qi and activating blood circulation, which were used for the treatment of hepatopathy by national medical masters.

Analysis on Menghe Physician Ma Peizhi’s Medication Rule in Prescriptions for Cough Based on Knowledge Discovery in Database / 中国中医药信息杂志

Objective To analyze the composing experience of Menghe physician Ma Peizhi for cough by TCM inheritance support system. Methods The prescriptions for cough of Ma Peizhi were collected, frequency and association of drugs were analyzed by using data mining methods such as revised mutual information, complex system entropy cluster and unsupervised hierarchical cluster. Results Based on the analysis of 57 prescriptions, the frequency of each herb and association rules among the herbs were computed, 18 core combinations and 9 new prescriptions were mined from the database. Conclusion Menghe physicians Ma Peizhi is well experienced in expelling wind and opening the inhibited lung, dissolving phlegm and relieving cough. TCM inheritance support system can be used to analyze clinical experience of old TCM doctor.

Analysis on the principle of the drug use ofMenghe physiciansMa-Peizhi based on apriori and clustering algorithm / 国际中医中药杂志

Objective To analyze the principle of the drug use ofMenghe PhysiciansMa-Peizhi by using the Traditional Chinese Medicine(TCM)inheritance support system.Methods The prescriptions for the commonly encountered diseases that used byMa-Peizhi were collected to build a database, and analyze by the unsupervised data mining methods, such as apriori algorithm, entropy clustering complex systems, from which we could get the frequency of the drugs, the association rules between drugs, the core drug combinations, and so on.Results Based on the analysis of 745 prescriptions, the most frequently used drugs were tuckahoe, chiretta, paenoiae alba, dried orangepeel and dioscoreae. The core drug combinations were “radix rehmanniae recen- salivia chinensis-ophiopogon root”, “teasel root-viscum album-achyranthes”, “menispermaceae-heracleum hemsleyanum michaux-gentiana macrophylla”, and “mulberry leaf-periostracum cicadae-the root of balloon flower”. The new prescriptions were “mulberry leaf-viter rotundifolia-batryticated silkworm-periostracum cicadae-the root of balloon flower”, “teasel root-viscum album- achyranthes- ramulus mori- periplocae”, and so on.ConclusionMenghe PhysiciansMa-Peizhi was well experienced in treating the commonly encountered diseases by agile diagnosis and treatment, and addition or subtraction of changes based on the classical prescriptions.

Analysis on Drug Combination Rule in Mutual Restraint Based on Apriori and Clustering Algorithm / 中国中医药信息杂志

Objective To investigate the drug combination of mutual restraint which is one of the application of seven different combination in drug in traditional Chinese medicine. Methods With the methods of association rules and complex system entropy clustering, we analyzed the drug combinations of mutual restraint that were collected from Compendium of Material Medica, to obtain the frequence of the single drug and drug combination of mutual restraint and the association rules between them. Results The single drugs with higher frequency are Rhizoma Coptidis, Fructus Crotonis, Rhei Radix Et Rhizoma, Azurite, Rhizoma Acori Tatarinowii, etc. The drug combinations with higher frequency are Azurite and Artemisia capillaries, Fructus Crotonis and Rhizoma Coptidis, Fructus Crotonis and Soybean etc. The associative drug combinations which confidence is 1 include “Indigo juice → Fructus Crotonis”,“Indigo juice → Rhizoma Coptidis”, etc. Conclusion The drug combinations of mutual restraint mainly include mineral drugs, antipyretics, purgatives, and toxic drugs.

Inhomogeneous magnetic resonance image segmentation by spatial model to fuzzy clustering / 医疗卫生装备

Fuzzy c-means (FCM) clustering algorithm is a popular model widely used in the segmentation of magnetic resonance image (MRI). The conventional FCM doesn't involve the spatial information of MRI and then unexpected segmentation results appear when it is applied to inhomogeneous MRI with noise and bias field. Modifying the objective function of FCM and introducing a variable as the parameter to control the tight degree of neighborhood effect present a spatial model to FCM clustering algorithm. The variable can reasonably use the spatial information of MRI. The experiment results show that the proposed algorithm can provide a powerful segmentation than the conventional FCM and others.