Proceedings of the 7th International Conference on Bioinformatics Research and Applications最新文献

Influenza Transmission Model by Dynamical Analysis and Cellular Automata 基于动态分析和元胞自动机的流感传播模型

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440076

P. Pongsumpun

引用次数: 0

Classification of Histopathology Images with Random Depthwise Convolutional Neural Networks 基于随机深度卷积神经网络的组织病理学图像分类

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440072

Yanan Yang, F. Farhat, Yunzhe Xue, F. Shih, Usman Roshan

{"title":"Classification of Histopathology Images with Random Depthwise Convolutional Neural Networks","authors":"Yanan Yang, F. Farhat, Yunzhe Xue, F. Shih, Usman Roshan","doi":"10.1145/3440067.3440072","DOIUrl":"https://doi.org/10.1145/3440067.3440072","url":null,"abstract":"The classification of whole slide images plays an important role in understanding and diagnosing cancer. Pathologists typically have to work through numerous pathology images that can be in the order of hundreds or thousands which takes time and is prone to manual error. Here we investigate an automated method based on a random depthwise convolutional neural network (RDCNN). In previous work this network has shown to achieve high accuracies for image similarity. We conjecture that for histopathology images similarity may play an important role in accurate classification of the images. We evaluate RDCNN against trained deep convolutional neural networks VGG16 and ResNet50 on four pathology image datasets. We find RDCNN to give the average highest accuracy across the four datasets. On two datasets RDCNN is significantly higher in accuracy and comparable in the others. We examine top similar images to a randomly selected one in the ISIC and Gleason datasets and see that it indeed most of the similar images belong to the same category as the query in the RDCNN feature space compared to ResNet50 and VGG16. For such histopathology datasets where similarity also implies same class membership we can expect RDCNN to be highly accurate and useful.","PeriodicalId":431179,"journal":{"name":"Proceedings of the 7th International Conference on Bioinformatics Research and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129451047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of SEIR Model to Predict Covid-19’s Early Stage in Hubei Province SEIR模型在湖北省新冠肺炎疫情早期预测中的应用

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440071

Tianmeng Huang

引用次数: 0

Identification of Autism Spectrum Disorder via an Eye-Tracking Based Representation Learning Model 基于眼动追踪表征学习模型的自闭症谱系障碍识别

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440078

Chen Xia, Kexin Chen, K. Li, Hongxia Li

{"title":"Identification of Autism Spectrum Disorder via an Eye-Tracking Based Representation Learning Model","authors":"Chen Xia, Kexin Chen, K. Li, Hongxia Li","doi":"10.1145/3440067.3440078","DOIUrl":"https://doi.org/10.1145/3440067.3440078","url":null,"abstract":"Autism spectrum disorder (ASD) is a lifelong developmental disorder characterized by repetitive, restricted behavior and deficits in communication and social interactions. Early diagnosis and intervention can significantly reduce the hazards of the disease. However, the lack of effective clinical resources for early diagnosis has been a long-standing problem. In response to this problem, we apply the recent advances in deep neural networks on eye-tracking data in this study to classify children with and without ASD. First, we record the eye movement data of 31 children with ASD and 43 typically developing children on four categories of stimuli to construct an eye-tracking data set for ASD identification. Based on the collected eye movement data, we extract the dynamic saccadic scanpath on each image for all subjects. Then, we utilize the hierarchical features learned from a convolutional neural network and multidimensional visual salient features to encode the scanpaths. Next, we adopt the support vector machine to learn the relationship between encoded pieces of scanpaths and the labels from the two classes via supervised learning. Finally, we derive the scores of each scanpath and make the final judgment for each subject according to the scores on all scanpaths. The experimental results have shown that the proposed model has a maximum classification accuracy of 94.28% in the diagnostic tests. Based on existing research and calculation models, dynamic saccadic scanpaths can provide promising findings and implications for ASD early detection. Furthermore, integrating more information of the scanpaths into the model and developing a more in-depth description of scanpaths can improve the recognition accuracy. We hope our work can contribute to the development of multimodal approaches in the early detection and diagnosis of ASD.","PeriodicalId":431179,"journal":{"name":"Proceedings of the 7th International Conference on Bioinformatics Research and Applications","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127318082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Characterization of the Perception of Occupational Risks of Health Personnel Associated with the Use of Personal Protective Equipment in Covid-19 in a Public Hospital 某公立医院新冠肺炎疫情中个人防护装备使用相关卫生人员职业风险认知特征分析

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440070

Ana Yamunaque, Ines Anzualdo, Vilma Arroyo, Braulio Espinoza, M. Chauca

{"title":"Characterization of the Perception of Occupational Risks of Health Personnel Associated with the Use of Personal Protective Equipment in Covid-19 in a Public Hospital","authors":"Ana Yamunaque, Ines Anzualdo, Vilma Arroyo, Braulio Espinoza, M. Chauca","doi":"10.1145/3440067.3440070","DOIUrl":"https://doi.org/10.1145/3440067.3440070","url":null,"abstract":"The research favors characterizing how the occupational risks of health personnel are perceived and the association with the use of personal protective equipment in Covid-19 in a public hospital, where in this time of pandemic, occupational risks are characterized and how they influence in the use of personal protective equipment (PPE), the versatility of suppliers in creating new protection elements. The objective was to determine the relationship between perception of occupational risks and the use of personal protective equipment in covid-19 in health personnel. The methodology was a correlational study, with a quantitative approach. As instruments, the occupational risk assessment of health personnel and the level of personal protective equipment were used; applied to a sample of 30 (health personnel) from a public hospital. The results were the findings perceived by health personnel. When evaluating correlation using Spearman's R, a significant relationship was found between the level of occupational hazards and the use of personal protective equipment (r = 0.498; p≤0.001). The conclusions were that there is a positive and significant relationship between the perception of occupational risks and the use of personal protective equipment in the health personnel of a public hospital. The usefulness was to demonstrate the influence of occupational health risks, it is important to develop new designs in the use of personal protective equipment. This helps health personnel with better protective equipment.","PeriodicalId":431179,"journal":{"name":"Proceedings of the 7th International Conference on Bioinformatics Research and Applications","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123298297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of High Fat and High Sugar Diet on Mouse Liver Redox Status 高脂高糖饮食对小鼠肝脏氧化还原状态的影响

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440069

Xinyi Zhao

引用次数: 0

Health Causal Probability Knowledge Graph: Another Intelligent Health Knowledge Discovery Approach 健康因果概率知识图:另一种智能健康知识发现方法

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440077

HongQing Yu

{"title":"Health Causal Probability Knowledge Graph: Another Intelligent Health Knowledge Discovery Approach","authors":"HongQing Yu","doi":"10.1145/3440067.3440077","DOIUrl":"https://doi.org/10.1145/3440067.3440077","url":null,"abstract":"Currently, most of the health-data research concentrates on applying Deep Learning technologies for prediction and reasoning. Deep Learning processes build the prediction model purely based on fitting weights on the raw data inside multiple neural layers, which is difficult to explain the prediction outputs. However, telling ‘WHY’ is crucial for healthcare research. The major difficulty to explain in Deep Learning models is a lack of knowledge-based analysis environment that not only can model the knowledge in a machine-understandable way but also can create causal probability relations inside the knowledge. In our research, we propose a Causal Probability Description Logic (CPDL) framework that extended the current Description Logic (DL). The key extension is to have a two-layer DL representation. One layer represents causality knowledge. The other layer takes observation inputs e.g. symptoms for generating a runtime probability knowledge graph based on the previous layer's knowledge. The CPDL framework can support probability-based causal reasoning tasks in a transparent and human-understandable way. CPDL can be easily implemented using existing programming standards such as OWL, RDF, SPARQL and probability network programming libraries. The experimental evaluations extract 383 common disease conditions from the UK NHS (National Healthcare Service) and enable automatically linked 418 condition terms from the DBpedia dataset. The CPDL-based knowledge graph can support disease prediction with traceable pieces of evidence behind the ranking results.","PeriodicalId":431179,"journal":{"name":"Proceedings of the 7th International Conference on Bioinformatics Research and Applications","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123585923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Analyze of SEIR Dengue Infectious Transmission Model with Vaccination SEIR登革热疫苗感染传播模型分析

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440068

Anusit Chamnan, P. Pongsumpun

引用次数: 0

Characterisation of the cell product obtained with the ‘ESVIEF System’ kit for isolation of stromal vascular fraction from human adipose tissue 使用“ESVIEF系统”试剂盒从人脂肪组织中分离基质血管组分获得的细胞产物的特性

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440079

E. Kostromina, P. Eremin, D. Kondratev, A. Veremeev, I. Gilmutdinova

{"title":"Characterisation of the cell product obtained with the ‘ESVIEF System’ kit for isolation of stromal vascular fraction from human adipose tissue","authors":"E. Kostromina, P. Eremin, D. Kondratev, A. Veremeev, I. Gilmutdinova","doi":"10.1145/3440067.3440079","DOIUrl":"https://doi.org/10.1145/3440067.3440079","url":null,"abstract":"Production technology and characteristics of the cell product obtained using the ‘ESVIEF System’ kit (developed by JoinTechCell LLC, Russian Federation) for isolation of a stromal vascular fraction from human adipose tissue are described. The use of subcutaneous fat as a source of stem and progenitor cells for regenerative medicine has become widespread during the last decade. The main advantage of using adipose tissue as a source of stem cells when compared with bone marrow is the lower invasiveness of the material sampling procedure during liposuction in addition to the significantly larger number of multipotent mesenchymal stromal cells obtained per unit of tissue volume. The development and implementation of devices for automation and standardisation of stem cell isolation from adipose tissue are important for the widespread use of stem cells in clinical practice. This work aimed to evaluate the effectiveness and safety of the cell production technology using the ‘ESVIEF System’ kit for isolation of a stromal vascular fraction from human adipose tissue. Adipose tissue samples obtained from patients during liposuction were used as clinical material. The obtained cell fractions were studied using microscopy, flow cytometry and cell culture methods. The viability of the stromal vascular fraction cells (nucleated) was 90.9 ± 0.3% with a total number of 0.81 ± 0.08 × 106 cells/ml of adipose tissue. The study showed that the ‘ESVIEF System’ kit that was developed for isolating stromal vascular fractions from human adipose tissue is a promising and safe technology for producing cell products.","PeriodicalId":431179,"journal":{"name":"Proceedings of the 7th International Conference on Bioinformatics Research and Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133248141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Study on Ultra-wideband Multiple Differential Recursive Imaging of stroke: A recursive brain imaging solution for stroke detection. 脑卒中的超宽带多重差分递归成像研究:脑卒中检测递归成像解决方案。

Proceedings of the 7th International Conference on Bioinformatics Research and Applications Pub Date : 2020-09-13 DOI: 10.1145/3440067.3440074

Zekun Zhang, Heng Liu

引用次数: 0