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Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences最新文献

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Mechanism Research and Application of Brain-computer Interface 脑机接口机理研究与应用
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3430085
Yunxin Zhang
{"title":"Mechanism Research and Application of Brain-computer Interface","authors":"Yunxin Zhang","doi":"10.1145/3429889.3430085","DOIUrl":"https://doi.org/10.1145/3429889.3430085","url":null,"abstract":"As a special human-computer interaction mode, brain-computer interface (BCI) has attracted more and more attention and become a research hotspot in the field of artificial intelligence and control, it has been widely studied and applied in many fields. This paper first introduces the formation and classification of Electroencephalogram (EEG) signals, the collection methods, the problems and the current solutions, then introduces several classical theories of core technologies and introduces some innovative algorithms. In addition, the application of BCI system in medical recovery and auxiliary work is introduced. Finally, the paper makes the expectation and prospect for the future development.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115848242","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
Power Spectral Estimation of short-term AF Recordings by Parametric Method Based on AR Model 基于AR模型的参数化短时自动对焦记录功率谱估计
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3429911
Yaru Yue, Hao Dang, Xingxiang Tao, Wei Zhou, Xiaoguang Zhou
{"title":"Power Spectral Estimation of short-term AF Recordings by Parametric Method Based on AR Model","authors":"Yaru Yue, Hao Dang, Xingxiang Tao, Wei Zhou, Xiaoguang Zhou","doi":"10.1145/3429889.3429911","DOIUrl":"https://doi.org/10.1145/3429889.3429911","url":null,"abstract":"With the aggravation of population aging, the number of atrial fibrillation (AF) has increased dramatically, seriously endangering human health. Therefore, in order to detect AF on wearable devices accurately, parametric power spectrum estimation (PSD) based on autoregressive (AR) model was used to extract and analyze the frequency-domain features of short-term AF recordings. By comparing classical PSD with parameter PSD based on AR model for short-term AF signals with baseline wandering removed, it was found that this algorithm can estimate real signals, and the PSD results of AF signals and sinus rhythm signals are distinct. Moreover, the influence of model order for PSD was analyzed. Simulation results show that the parametric PSD based on AR model can accurately extract the frequency-domain characteristics of AF signals and is an effective method.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121952042","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
Mult-threshold Object Segmentaton Algorithm on Low-contrast and Noisy Biomedical Images 低对比度和噪声生物医学图像的多阈值目标分割算法
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3429914
Ronghao Wang, Dingding Jian, Yuying Sun
{"title":"Mult-threshold Object Segmentaton Algorithm on Low-contrast and Noisy Biomedical Images","authors":"Ronghao Wang, Dingding Jian, Yuying Sun","doi":"10.1145/3429889.3429914","DOIUrl":"https://doi.org/10.1145/3429889.3429914","url":null,"abstract":"Object detection and segmentation is an important direction in biological image processing. Traditional thresholding and labeling methods as well as machine learning methods are the two predominant ways to solve this problem. In this article, a multi-threshold algorithm doing cell segmentation is developed and applied on Fluo-N2DH-GOWT1 dataset[1-2], which contains low-contrast and noisy biomedical images. Besides, U-net is also utilized and the results of U-net as well as multi-threshold algorithm are compared to better illustrate the distinctions of the two algorithms.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116766221","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
Research on batching strategy of medical orders based on Canopy-K-means two-stage clustering algorithm 基于Canopy-K-means两阶段聚类算法的医嘱批处理策略研究
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3429930
Yufeng Zhuang, Jingwen Han, Yanzhu Hu
{"title":"Research on batching strategy of medical orders based on Canopy-K-means two-stage clustering algorithm","authors":"Yufeng Zhuang, Jingwen Han, Yanzhu Hu","doi":"10.1145/3429889.3429930","DOIUrl":"https://doi.org/10.1145/3429889.3429930","url":null,"abstract":"With the sharp increase in the number of orders and the amount of dismantling and sorting in the pharmaceutical logistics center, how to save labor in a limited time and improve the efficiency of sorting orders for dismantling is a problem that needs to be solved urgently in the field of medicine circulation. This article focuses on the issue of order batching strategy based on the \"delivery to person\" picking system in the pharmaceutical industry to improve the efficiency of picking. Based on the characteristics of pharmaceutical orders and related policies, the number of identical items between the two orders is used as the order coupling factor to establish the order batching model. In order to solve the model, this paper proposes the Canopy-k-means two-stage clustering algorithm in which the Canopy algorithm is used to coarsely cluster the orders to reduce the dimensionality firstly, and then the K-means clustering algorithm is run to subdivide the batch. In addition, the MATLAB platform is used to simulate and verify the algorithm, the implementation effects of the algorithm and the first come first service (FCFS) algorithm and the K-means clustering algorithm are compared, and the effectiveness of the algorithm in terms of clustering effect and operating efficiency is verified.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124833211","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
Analysis and Visualization of Novel Coronavirus Pneumonia Based on Python 基于Python的新型冠状病毒肺炎分析与可视化
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3430296
Feng Guo, Tianmeng Liu, Ya-ning Lei, Tong Li, Renbin Zhan
{"title":"Analysis and Visualization of Novel Coronavirus Pneumonia Based on Python","authors":"Feng Guo, Tianmeng Liu, Ya-ning Lei, Tong Li, Renbin Zhan","doi":"10.1145/3429889.3430296","DOIUrl":"https://doi.org/10.1145/3429889.3430296","url":null,"abstract":"Objective To study the rule of Chinese medicine prescription According to the prescription novel coronavirus pneumonia; to provide reference for the treatment of epidemic diseases. Methods Through crawling 227 prescriptions of Xinguan TCM collected by Huabing data website intelligent TCM big data platform, we analyzed the web page data by using word cloud analysis, data visualization and the third-party library lxml and request of Python. Results High frequency of drug use of traditional Chinese medicine are: Huoxiang, Atractylodes, Platycodon, honeysuckle, astragalus, Scutellaria, Atractylodes macrocephala, etc. The analysis of clinical symptoms showed that the most common symptoms were fatigue, fever, white fur, cough, chest tightness, diarrhea and so on. Hebei, Sichuan, Heilongjiang, Gansu and other provinces provide more. Conclusion The novel coronavirus pneumonia and almond novel coronavirus pneumonia treatment are better. The results showed that the effective prescriptions and fever, fatigue and other common clinical manifestations, as well as the provinces with higher prescriptions, have important reference significance for the follow-up development of the new crown pneumonia.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125768504","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
Construction and Exploration of Information Interconnection in a Hospital in the Guangdong-Hong Kong-Macao Greater Bay Area 粤港澳大湾区某医院信息互联建设与探索
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3429928
Qunqun Zhang, Xin Zhou, Qiri Wu
{"title":"Construction and Exploration of Information Interconnection in a Hospital in the Guangdong-Hong Kong-Macao Greater Bay Area","authors":"Qunqun Zhang, Xin Zhou, Qiri Wu","doi":"10.1145/3429889.3429928","DOIUrl":"https://doi.org/10.1145/3429889.3429928","url":null,"abstract":"The interconnection of hospital information systems is a technology that must be overcome in the development of my country's health informatization. The \"Outline of Development Plan for the Guangdong-Hong Kong-Macao Greater Bay Area\" has played a positive role in promoting the development of the Greater Bay Area. Comprehensive interconnection and information sharing can promote the improvement of medical services and the innovation of medical technology. The Fifth Affiliated Hospital of Sun Yat-sen University adheres to the goal of facing the frontiers of medicine, facing the strategy of healthy China and local economic and social needs, and facing the goal of a national regional medical center in the Guangdong-Hong Kong-Macao Greater Bay Area. This article introduces the basic situation and information construction process of the five hospitals' medical institutions, and introduces the construction of data resource standardization, interconnection standardization and infrastructure construction. On the basis of the above innovations, the application effects of interconnection are introduced, and the highlights of our hospital and the exploration of technological innovation are described.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122700542","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
Clinical Application of Intelligent Prediction Model for Atrial Fibrillation in Hypertensive Patients 高血压患者心房颤动智能预测模型的临床应用
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3429933
Min Zhang, Huiying Yang, Shulong Zhang, Xue-yao Feng, Zumin Wang, Jing Qin
{"title":"Clinical Application of Intelligent Prediction Model for Atrial Fibrillation in Hypertensive Patients","authors":"Min Zhang, Huiying Yang, Shulong Zhang, Xue-yao Feng, Zumin Wang, Jing Qin","doi":"10.1145/3429889.3429933","DOIUrl":"https://doi.org/10.1145/3429889.3429933","url":null,"abstract":"Hypertension is one of the most significant risk factors for atrial fibrillation (AF). However, few effective methods are available to support accurate prediction on the potential risk of atrial fibrillation among hypertensive patients currently. The aim of this paper is to illustrate a machine learning technology for constructing an atrial fibrillation intelligent prediction model. Eventually, the model can be employed to predict the risk of atrial fibrillation in hypertensive patients. A total of 2,067 diagnosed hypertensive patients (including 721 hypertensive patients complicated with atrial fibrillation) by Heart Center of Affiliated Zhongshan Hospital of Dalian University from January 2015 to January 2018 were enrolled in this study. As result, the atrial fibrillation prediction model was constructed based on the C5.0 decision tree classification algorithm. Moreover, compared with other machine learning classification algorithms, C5.0 has similar performance to random forest (RF), but is better than support vector machine(SVM), Logical Regression(LR), CHAID, and K nearest neighbor(KNN) classification algorithms. The proposed predict model has high accuracy of atrial fibrillation risk prediction for hypertension patients.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125360686","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
MSU-Net: A multi-scale U-Net for retinal vessel segmentation MSU-Net:用于视网膜血管分割的多尺度U-Net
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3430295
Zhengjin Shi, Tianyu Wang, Feng Xie, Zheng Huang, Xinyu Zheng, Wenjiao Zhang
{"title":"MSU-Net: A multi-scale U-Net for retinal vessel segmentation","authors":"Zhengjin Shi, Tianyu Wang, Feng Xie, Zheng Huang, Xinyu Zheng, Wenjiao Zhang","doi":"10.1145/3429889.3430295","DOIUrl":"https://doi.org/10.1145/3429889.3430295","url":null,"abstract":"Retinal vessel segmentation is widely used in the diagnosis of eye diseases, and the effect of segmentation plays a crucial role in whether doctors can correctly diagnose diseases. To further improve the accuracy of the automatic segmentation method, a network structure named Multi-Scale U-Net (MSU-Net) based on deep learning is proposed in this paper. The network combines Atrous Spatial Pyramid Pooling (ASPP) module to extract multi-scale information, making the U-Net more suitable for segmentation of complex and changeable vessel structures. We evaluate the network on two public databases, DRIVE and STARE. The Accuracy (ACC), Sensitivity (SEN), Specificity (SPE) and Dice coefficient on the DRIVE database are 0.9667, 0.8159, 0.9805 and 0.8059, respectively. These indicators are respectively 0.9732, 0.8272, 0.9866 and 0.8400 on the STARE database. Experiments show that the network has excellent segmentation results, and has state-of-the-art performance indicators on the STARE database, which fully proves the outstanding performance of the network.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131091921","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
A Feature Extraction Method to Improve the Classification Effect of N1 and REM in Sleep Periods 一种提高睡眠阶段N1和REM分类效果的特征提取方法
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3429926
Xiaobo Li
{"title":"A Feature Extraction Method to Improve the Classification Effect of N1 and REM in Sleep Periods","authors":"Xiaobo Li","doi":"10.1145/3429889.3429926","DOIUrl":"https://doi.org/10.1145/3429889.3429926","url":null,"abstract":"Non-linear feature extraction is an effective method for processing EEG signal. Sample entropy, KC complexity and correlation dimension of EEG combined with the machine learning methods can get a good result in automatic sleep staging. However, due to the similar activity characteristics of EEG during light sleep N1 and REM, the discrimination of above methods in these two phases is reduced. That the brain is relatively active and sawtooth waves appear in REM will cause the amplitude's changes of EEG signal are dissimilar. This article proposes an improved feature extraction method based on the amplitude in order to improve the recognition effect of N1 and REM. Correlation dimension and sample entropy of EEG in N1 and REM are compared with the improved method so the effectiveness of the method introduced in this essay can be verified.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128179953","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
Review of the Application of Blockchain Technology in Traditional Chinese Medicine Field 区块链技术在中医药领域的应用综述
Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences Pub Date : 2020-09-11 DOI: 10.1145/3429889.3429932
Shirui Zhou, Hui Sheng, Jingang Ma, Xiaochun Han
{"title":"Review of the Application of Blockchain Technology in Traditional Chinese Medicine Field","authors":"Shirui Zhou, Hui Sheng, Jingang Ma, Xiaochun Han","doi":"10.1145/3429889.3429932","DOIUrl":"https://doi.org/10.1145/3429889.3429932","url":null,"abstract":"The concept of blockchain has received a lot of attention and research since it was first proposed in 2008. With the popularization and development of blockchain technology, its huge development opportunities in the field of Traditional Chinese Medicine(TCM) have gradually revealed. This article studies the development path and technical characteristics of blockchain, analyzes the current research status of application of blockchain technology in medical field. It also summarizes the application and future research directions of blockchain technology in four typical TCM fields: TCM big data safe storage, Chinese medicine traceability, TCM electronic medical record privacy protection, TCM cloud health system and wearable devices. It is hoped that this paper can provide useful reference for relevant research.","PeriodicalId":315899,"journal":{"name":"Proceedings of the 1st International Symposium on Artificial Intelligence in Medical Sciences","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133121564","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: 2
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