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2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)最新文献

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Adaptive Noise-Reduction Algorithm for Diaphragm Electromyography Based on Linear Prediction 基于线性预测的膈肌电图自适应降噪算法
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061294
Lingxi Chen, Yuan-da Xu, Bin Li, Hongqiang Mo
{"title":"Adaptive Noise-Reduction Algorithm for Diaphragm Electromyography Based on Linear Prediction","authors":"Lingxi Chen, Yuan-da Xu, Bin Li, Hongqiang Mo","doi":"10.1109/ISBP57705.2023.10061294","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061294","url":null,"abstract":"Diaphragm electromyography (EMGdi) collected by esophageal electrodes can provide important information for the assessment of the respiratory system. But it is vulnerable to electrocardiogram (ECG) interference. It is pointed out that the autocorrelation function of EMGdi is significantly different from that of ECG. And accordingly, a filter based on linear prediction is proposed to suppress the ECG interference. The coefficients of the filter are adjusted on line so as to adapt to different subjects or the slow change of the autocorrelation function of the same subject over time. The filter is applied to clinically acquired signals, and the results demonstrate that it can effectively suppress the ECG interference, and the filtered EMGdi is in a good synchronization with the transdiaphragmatic pressure (Pdi).","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123880423","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
Classification and Processing of MIT-BIH Arrhythmia-Based on BP Algorithm 基于BP算法的MIT-BIH心律失常分类与处理
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061303
Fumin Mi, Baixuan Li, Xiaojie Cheng, Yunjie Zhao, Minyi Li, Jin Jing
{"title":"Classification and Processing of MIT-BIH Arrhythmia-Based on BP Algorithm","authors":"Fumin Mi, Baixuan Li, Xiaojie Cheng, Yunjie Zhao, Minyi Li, Jin Jing","doi":"10.1109/ISBP57705.2023.10061303","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061303","url":null,"abstract":"ECG recognition is of great significance to the diagnosis of heart diseases. Based on the data of the MIT-BIH Arrhythmia Database, a more accurate ECG signal map was extracted using wavelet transform, a BP neural network was constructed for pattern recognition, and five types of arrhythmia-sinus arrhythmia, premature beats, Yibo, sinoatrial block, and atrial block. And compared with the BP network using SVM and K nearest neighbor algorithm, it is found that the BP network performs better.","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"11 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125643619","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
Hybrid Multistage Feature Selection Method and its Application in Chinese Medicine 混合多阶段特征选择方法及其在中医中的应用
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061301
Ming Liu, Jianqiang Du, Zhiqing Li, Jigen Luo, Bin Nie, Mengting Zhang
{"title":"Hybrid Multistage Feature Selection Method and its Application in Chinese Medicine","authors":"Ming Liu, Jianqiang Du, Zhiqing Li, Jigen Luo, Bin Nie, Mengting Zhang","doi":"10.1109/ISBP57705.2023.10061301","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061301","url":null,"abstract":"The experimental data on traditional Chinese medicine efficacy has many irrelevant and redundant features, and different feature combinations have different effects. Therefore, we propose a hybrid multistage feature selection algorithm based on approximate Markov blanket and improved black widow algorithm. The first stage remove irrelevant features by the maximum information coefficient. The second stage delete redundant features from clustered searched by approximate Markov blanket by Lasso algorithm to avoid information loss. The third stage search the optimal feature subset by improved black widow algorithm that used the fast reproduction strategy, the child eating mother strategy and the population restriction strategy. The proposed approach is tested on the basic material data of traditional Chinese medicine and 9 UCI datasets, and compared with other feature selection algorithms. The experimental results show that the algorithm can obtain a small number of feature subsets with high accuracy, and has good time performance.","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121144914","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
Glucose Prediction Based on the Recurrent Neural Network Model 基于递归神经网络模型的血糖预测
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061295
Yilin Zhang
{"title":"Glucose Prediction Based on the Recurrent Neural Network Model","authors":"Yilin Zhang","doi":"10.1109/ISBP57705.2023.10061295","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061295","url":null,"abstract":"An advanced convolutional neural network architecture for forecasting blood glucose is proposed in this paper. Four different measures are introduced in this essay, including Glucose, Meal, Insulin, and Time of the day, which are denoted as G, M, I, and T for short. Past 2-hour historical data of individuals are exploited to predict the future glucose level in 30 minutes with high accuracy. To verify the effectiveness of the blood glucose prediction model, three major methods have been displayed and compared. To be more specific, Recurrent Neural Network (RNN) was the better model for forecasting blood glucose, compared with Neural Network Predictive Glucose (NNPG) and Support Vector Regression (SVM). The metrics of evaluation are Root-Mean-Square deviation (RMSE) and Mean Absolute Relative Difference (MARD). The average of the best RMSE is 7.75, which is largely better than those of the other two models. This result shows the superior performance of RNN in accurate glucose prediction.","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126033481","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
Drug Resistance Testing Using Electrical Impedance Counting Method 电阻抗计数法耐药试验
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061299
Jindai Huang, Dianchen Zhang
{"title":"Drug Resistance Testing Using Electrical Impedance Counting Method","authors":"Jindai Huang, Dianchen Zhang","doi":"10.1109/ISBP57705.2023.10061299","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061299","url":null,"abstract":"Traditional methods for testing drug sensitivity values include broth dilution methods including micro broth dilution and macro broth dilution methods, agar dilution methods, E-test methods and paper diffusion methods[1]. These traditional methods have a common shortcoming, that is, the test often takes a long time to obtain drug sensitivity results, which can lead to missed diagnosis, misdiagnosis and delayed treatment.This paper describes how the electrical impedance counting method was used for the study of drug sensitivity testing and what advantages it has over traditional drug sensitivity testing. The impedance counting method still uses the broth dilution method and the existing parameter MIC (minimum inhibitory concentration)[1], which is the most relied upon parameter to guide the use of antibiotics, as an indicator, with the Coulter principle[2] technique as the underlying principle, and the IT system to collect, process and analyze the data. The MIC values were obtained by calculating the number of bacteria at different doses of antibiotics, analyzing the graphical changes such as growth indices, using software algorithms and referring to the CLSI M100[3] standard to discriminate the drug susceptibility of bacteria. The results show that the electrical impedance counting method will provide us with a more rapid and effective method for drug sensitivity analysis, and can be used in medical institutions and related medical industries for drug sensitivity analysis, which is of great significance for rapid and accurate clinical drug use and new antibiotic research.","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134517914","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 virtual reality technology in post-traumatic stress disorder 虚拟现实技术在创伤后应激障碍中的应用
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061313
Jinxiu Zhang, Xunbing Shen
{"title":"Application of virtual reality technology in post-traumatic stress disorder","authors":"Jinxiu Zhang, Xunbing Shen","doi":"10.1109/ISBP57705.2023.10061313","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061313","url":null,"abstract":"Post-traumatic stress disorder (PTSD) is a series of long-lasting mental disorders caused by individuals experiencing or witnessing life-threatening events, which are characterized by the presence of three main symptom groups: persistent fear memory, hyperarousal and avoidance, causing severe social disorders and health damage to patients. With the development of computer science and technology, emerging virtual reality technology provides a new means of treatment for common mental illness. Based on the analysis of the pathogenesis of PTSD and the superiority of virtual reality technology, this paper reviews the application of virtual reality technology in the treatment of PTSD in recent years at home and abroad. We hope to bring inspiration for the combination of virtual reality technology with traditional therapy and its innovative application for better diagnosis and treatment of PTSD.","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129760601","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
ISBP 2023 Cover Page ISBP 2023封面页
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/isbp57705.2023.10061300
{"title":"ISBP 2023 Cover Page","authors":"","doi":"10.1109/isbp57705.2023.10061300","DOIUrl":"https://doi.org/10.1109/isbp57705.2023.10061300","url":null,"abstract":"","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"13 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120835752","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
High-efficiency drug design research based on virtual high-throughput screening 基于虚拟高通量筛选的高效药物设计研究
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061293
Haonan Zhou
{"title":"High-efficiency drug design research based on virtual high-throughput screening","authors":"Haonan Zhou","doi":"10.1109/ISBP57705.2023.10061293","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061293","url":null,"abstract":"Drug screening is crucial in the entire pharmaceutical chain. There are about 3500W of known structural drug compound molecules in the world. The massive amount of data has led to an enormous screening task for a single protein target. Therefore, how accelerating the speed of high-throughput screening is an urgent problem. We combine the advantages of computer CPU multi-core for parallel optimization of D3DOCKxb to achieve accelerated drug screening.","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130833442","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
ECG arrhythmias Classification with a Graph Bispectrum method 基于图双谱法的心电心律失常分类
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061314
Yang Shiyilin, Shao Jie, Yang Xin, Chen Xin, Wang Xingxing
{"title":"ECG arrhythmias Classification with a Graph Bispectrum method","authors":"Yang Shiyilin, Shao Jie, Yang Xin, Chen Xin, Wang Xingxing","doi":"10.1109/ISBP57705.2023.10061314","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061314","url":null,"abstract":"Heart disease is leading killers of human beings. Recognizing and categorizing Electrocardiogram (ECG) signals is crucial for early heart and cardiovascular disease prevention. A novel classification approach for ECG Arrhythmias based on Graph Bispectrum (GBispec) is proposed. First, the ECG signal is converted from the time domain to the Graph domain by using Graph Fourier Transform (GFT); Then, referring to the traditional bispectrum algorithm, the GFT results of ECG are converted into GBispec; Then, extract the graph features of Graph Integral Bispectrum (GIB), and use Deep Neural Networks(DNN) to process the GIB results. 4 different types of ECG signals are classified. Experiments results show that proposed method is effective in classification.","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121428731","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
Depth-First Uncertain Frequent Itemsets Mining based on Ensembled Conditional Item-Wise Supports 基于集成条件项支持的深度优先不确定频繁项集挖掘
2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP) Pub Date : 2023-01-06 DOI: 10.1109/ISBP57705.2023.10061307
Wanyong Tian, Fuqiang Li, Yibo Liu, Zichen Wang, Zhang Tao
{"title":"Depth-First Uncertain Frequent Itemsets Mining based on Ensembled Conditional Item-Wise Supports","authors":"Wanyong Tian, Fuqiang Li, Yibo Liu, Zichen Wang, Zhang Tao","doi":"10.1109/ISBP57705.2023.10061307","DOIUrl":"https://doi.org/10.1109/ISBP57705.2023.10061307","url":null,"abstract":"Uncertain frequent pattern mining is usually challenged by the single probabilistic frequent threshold or the single expected support as the measurements of frequent itemsets. A promising solution based on multiple expected minimum support has been introduced in more recent studies to distinguish the mining values of each item, but the intrinsic combinatorial explosion still limited this strategy to be further improved for more generic scenarios. In this paper, a novel mining scheme for uncertain frequent itemsets is proposed. By ensembling multiple conditional item-wise supports, the problems of information redundancy as well as loss caused by a single probabilistic frequent threshold can be effectively improved. Furthermore, by using a variety of pruning strategies based on the property of sorted downward closure and the concept of least minimum probabilistic frequent threshold, an UFP-ECIS (Uncertain Frequent Pattern Mining with Ensembled Conditional Item-wise Supports) algorithm is also introduced. Substantial experiments have been proved to demonstrate that the proposed mining scheme and algorithm has enhanced the information precision of the uncertain frequent itemsets mining.","PeriodicalId":309634,"journal":{"name":"2023 International Conference on Intelligent Supercomputing and BioPharma (ISBP)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126460151","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
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