2022 2nd International Conference on Bioinformatics and Intelligent Computing最新文献_第6页

Design and Architecture of Local Health Platform 本地健康平台的设计与架构

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524515

Zhao Wang, J. Shan, Yawen Pan

引用次数: 0

Improving Latent Factor Analysis via Self-supervised Signal Extracting 基于自监督信号提取的潜在因子分析改进

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524586

Y. Huang, Zhuliang Yu

引用次数: 0

Forecasting CO2 Emission from Thermal Power Production in Beijing-Tianjin-Hebei by Using GM (1,1) Model 基于GM(1,1)模型的京津冀地区火力发电CO2排放预测

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524593

Deng Pan

引用次数: 0

The construction of drought disaster early warning model in apple orchard 苹果园干旱灾害预警模型的构建

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524606

Zhaoyang Yuan, Runze Wang, Dongjian Shen, Shu-han Cheng, Zhijun Wang

引用次数: 0

Intelligent Perception Recognition of Multi-modal EMG Signals Based on Machine Learning 基于机器学习的多模态肌电信号智能感知识别

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524576

Mingchuan Zhang, Zuhao Wang, Guannan Meng

{"title":"Intelligent Perception Recognition of Multi-modal EMG Signals Based on Machine Learning","authors":"Mingchuan Zhang, Zuhao Wang, Guannan Meng","doi":"10.1145/3523286.3524576","DOIUrl":"https://doi.org/10.1145/3523286.3524576","url":null,"abstract":"Surface Electromyography (sEMG) signals directly and objectively reflect the activity of human muscles. As a convenient non-invasive EMG detection method, it is widely used in the field of human action recognition. First, this paper performs active segment detection on the sEMG data collected by the MYO bracelet to extract effective active segments. Subsequently, we extracted five time-domain features from the active segment signal, including the root mean square value, the length of the waveform, the number of zero-crossing points, the mean absolute value, and the maximum-minimum value. Four classifiers, i.e, K nearest neighbor (KNN), support vector machine (SVM), decision tree (DT) and random forest (RF) are used to classify and recognize the extracted sEMG. The highest correct rate is random forest with a value of 82%. Therefore, this paper further extracts the frequency domain characteristics of the signal including the Fourier transform and Willison amplitude. We added 4 models for comparative experiments, including gradient boosting (GB), Gaussian Naive Bayes (NB), linear discriminant analysis (LDA) and logistic regression (LR). The final experimental conclusion show that the effects of the four classifiers have been significantly improved. The best result is SVM for intelligent perception recognition of multi-modal EMG signals, with an accuracy rate of 90% and an F1 score of 0.87.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123276465","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

Tobacco Traceability and Storage Scheme Based on IPFS+ Consortium Chain 基于IPFS+联盟链的烟草可追溯与储存方案

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524547

YanMei Zhu, Zhonghua Liu, Zhijian Wang, LongXiang Yang, KeShu Peng, Kai Liu

引用次数: 0

Correlation analysis of blood lipid metabolism level and stomach cancer based on information system health data 基于信息系统健康数据的血脂代谢水平与胃癌的相关性分析

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524531

YuXin Li, Yong-min Feng

{"title":"Correlation analysis of blood lipid metabolism level and stomach cancer based on information system health data","authors":"YuXin Li, Yong-min Feng","doi":"10.1145/3523286.3524531","DOIUrl":"https://doi.org/10.1145/3523286.3524531","url":null,"abstract":"Stomach cancer used to be the most common tumor in humans all over the world. In recent decades, the incidence of stomach cancer has shown a downward trend in the world, but it was still one of the most common malignant tumors in humans, and the incidence was highest in East Asia. With the continuous improvement of the hospital information system, clinical health data will continue to be accumulated. With the help of a large amount of health data, we can make a comprehensive data comparison between healthy people and stomach cancer patients. In this study, the blood lipid metabolism levels of healthy people and stomach cancer patients were compared with the help of medical health data. In this study, 650 patients with stomach cancer were selected as the experimental group, and 1165 patients who went to the hospital for health check-ups during the same period were also selected as the control group. In this study, by analyzing the correlation between the blood lipid detection data of stomach cancer patients and healthy people, it was found that, serum total cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, apolipoprotein AI and apolipoprotein B in normal healthy people were significantly higher than those in stomach cancer patients. Through this study, the differences in blood lipid metabolism between stomach cancer patients and healthy people were further clarified. By evaluating the metabolic level of blood lipids in patients, it is of great significance for early screening of stomach cancer, nutritional treatment, improvement of prognosis, and improvement of patients' quality of life.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128465027","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

Preliminary denoising by 3D U-Net in image domain for low dose CT images 低剂量CT图像的三维U-Net图像域初步去噪

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524571

Xiaofu Song, Yu Han, Xiaoqi Xi, Lei Li, Linlin Zhu, Shuangzhan Yang, Mengnan Liu, Siyu Tan, Bin Yan

{"title":"Preliminary denoising by 3D U-Net in image domain for low dose CT images","authors":"Xiaofu Song, Yu Han, Xiaoqi Xi, Lei Li, Linlin Zhu, Shuangzhan Yang, Mengnan Liu, Siyu Tan, Bin Yan","doi":"10.1145/3523286.3524571","DOIUrl":"https://doi.org/10.1145/3523286.3524571","url":null,"abstract":"Low dose CT (LDCT) by reducing the X-ray tube current is of huge significance during clinical scanning. However, low-dose CT images often have strong noise and artifacts, which affects the image quality and diagnostic performance. LDCT noise reduction methods based on deep learning have recently achieved good results in improving image quality. Since the reconstructed CT image itself is 3D, in this paper a LDCT denoising method based on 3D U-Net is proposed to combine the 3D spatial information by 3D convolution directly, instead of processing 2D slices from 3D volume data. Therefore, the image change continuity between the adjacent slices is guaranteed. In addition, multiple down-sampling operations in the network, which can reduce the number of parameters of the 3D network, help the network to train. The experimental results show that the proposed method can effectively preserve the structural and texture information of normal NDCT images and significantly suppress the image noise and artifacts, achieving better performance in both quantification and visualization. Compared with LDCT images without denoising, the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of the processed images were improved by 12.18 dB and 0.35 dB, respectively.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121973725","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

Study on reference-based FASTQ genome sequences compression 基于参考的FASTQ基因组序列压缩研究

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524511

Wenlong Li, Jianhua Chen, Zhiwen Lu

引用次数: 0

Research on 10-year Beast Cancer Survival Prediction Model Based on Mixed Feature Selection 基于混合特征选择的10年兽癌生存预测模型研究

2022 2nd International Conference on Bioinformatics and Intelligent Computing Pub Date : 2022-01-21 DOI: 10.1145/3523286.3524578

Yufang Deng

引用次数: 0