Proceedings of the 2021 International Conference on Intelligent Medicine and Health最新文献

{"title":"Compared the Efficacy and Safety between Intravenous Vedolizumab and Subcutaneous Formulation Therapy in Inflammatory Bowel Disease: A Meta-Analysis","authors":"Jiayi Zhang, Zihui Zou","doi":"10.1145/3484377.3484394","DOIUrl":"https://doi.org/10.1145/3484377.3484394","url":null,"abstract":"Traditional treatment method for moderate or severe inflammatory bowel disease (IBD) is intravenous (IV) vedolizumab to suppression α4β7 integrin. This study aims to assess the efficacy and safety of subcutaneous (SC) vedolizumab compared to IV vedolizumab in IBD. We searched PubMed, Embase and Cochrane library. All randomized controlled trials (RCTs) were included, which compared SC vedolizumab to IV vedolizumab treatment in IBD patients. Our main endpoints are remission at week 52, durable remission and treatment-emergent adverse events (TEAEs). The Review Manager 5.4 was used in the meta-analysis. Two RCT studies were included with a total of 172 participants with ulcerative colitis (UC). Two studies (N=172 participants) assessed the odds ratio (OR) of remission at week 52, durable remission and TEAEs during treatment. After analysis, the data of these studies showed there were significant difference in related TEAEs of SC vedolizumab compared with IV vedolizumab treatment (OR=2.48 [95%CI, 1.09-5.61], P=0.03). In both SC and IV vedolizumab treatment, there didn't have death events. And there were no significant difference in clinical remission and endoscopic improvement at week 52 and durable remission (P>0.05). SC vedolizumab treatment has similar efficacy compared to IV vedolizumab treatment in IBD patients. But SC vedolizumab treatment has more related-TEAEs. For safety of SC vedolizumab treatment in IBD patients need further research.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"100 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120904326","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}

{"title":"Drug-Resistant States in Response to EGFR Tyrosine Kinase Inhibitors in Non-Small-Cell Lung Cancer","authors":"Ruilong Chen, Risha Na","doi":"10.1145/3484377.3484393","DOIUrl":"https://doi.org/10.1145/3484377.3484393","url":null,"abstract":"Non-small-cell lung cancer (NSCLC) is the most abundant form of lung cancer. There is a need for targeted therapies for NSCLC that would obviate the risk of adverse effects associated with traditional chemotherapy. EGFR tyrosine kinase inhibitors erlotinib and gefitinib have been used successfully as targeted drug therapies for NSCLC, but NSCLC tumours may develop resistance to these inhibitors. In this study, we reanalysed publicly available single-cell RNA-Seq datasets to identify whether the drug-resistant states in erlotinib and gefitinib-treated cell model of NSCLC share common transcriptional responses. Further work is needed to determine whether gefitinib and erlotinib-resistance may be underlined by common transcriptional pathways.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128430318","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}

{"title":"A 3D CNN-based Multi-task Learning for Cataract screening and left and right eye classification on 3D AS-OCT images","authors":"Zunjie Xiao, Xiaoqin Zhang, Risa Higashita, Wan Chen, Jin Yuan, Jiang Liu","doi":"10.1145/3484377.3484378","DOIUrl":"https://doi.org/10.1145/3484377.3484378","url":null,"abstract":"Cataract is the leading cause for visual impairment and blindness. Cataract screening can effectively improve the recovery rate of cataract, and the left and right eye classification is a significant step in cataract screening. Anterior segment optical coherence tomography (AS-OCT) is a non-contact, high-resolution ophthalmic imaging technique, which can quickly obtain pathological information of cataract and left and right eye position information through three-dimensional (3D) imaging. In order to improve the efficiency of cataract screening, we propose a multi-task three-dimensional convolutional neural network (MT-CNN) for automatic cataract detection and left and right eye classification simultaneously based on the 3D AS-OCT images. The MT-CNN is designed based on the hard sharing mechanism, achieving better performance with fewer parameters than single-task learning. The results on an AS-OCT image dataset show that the 3D CNN model obtains better classification performance than the 2D CNN model. Compared with the single-task 3D CNN model, MT-CNN achieves higher accuracy under the premise of greatly parameters reduction and computational complexity reduction.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"51 348 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126152285","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}

{"title":"Intelligent and Automatic Treatment Planning System for Low-Dose-Rate Brachytherapy of Malignant Hepatic Tumors","authors":"Jianjun Zhu, H. Luo, Cheng Wang, Jian Lu, G. Teng","doi":"10.1145/3484377.3484385","DOIUrl":"https://doi.org/10.1145/3484377.3484385","url":null,"abstract":"The inefficient manual treatment planning of low-dose-rate brachytherapy for the malignant hepatic tumor is still the dominant clinical application. The purpose of our work is to develop an intelligent and efficient treatment planning system (TPS) that can segment multiple organ targets accurately and quickly, generate optimal seed implantation plans with fewer manual interactions, in the meantime, automatically avoid vital organ puncture. The TPS consists of three main modules, which are the abdominal multi-organ segmentation module, inverse dose planning module, and puncture pathway selection module. In the segmentation module, we adopt the latest deep learning-based model, which can automatically segment the hepatic tumor and 13 abdominal organs by training on public datasets and the datasets we collected. In the dose planning model, a novel parameterization strategy for the implantation plan is proposed. The parameterization strategy dramatically decreases the number of parameters needed to define the implantation plan and enables the fast simulated annealing algorithm to explore a possible solution. The puncture pathway selection is coupled within the optimization algorithm by rejecting clinically unacceptable ones when generating new potential solutions, which enables automatical puncture pathway selection during inverse planning. Hepatic malignant tumors cases are used to test the performance of our TPS, and the optimization time and cost value of each FSA iteration were recorded. The proposed method achieved ideal dose distribution and high conformity in the clinical practice within 1-4 minutes according to the size of the computational phantom and the number of used seeds. In addition, the consistency in the repetition test and the decreasing tendency of cost values from each iteration demonstrated the convergence of the algorithm. More importantly, our TPS can generate an ideal implantation plan in minutes without any medical physicists’ involvement.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127237905","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}

{"title":"A Meta-Analysis of Social Media Usage with Stress, Anxiety, and Depression","authors":"Junyu Ma","doi":"10.1145/3484377.3487041","DOIUrl":"https://doi.org/10.1145/3484377.3487041","url":null,"abstract":"Since the social media burst, over 3.6 billion people have had access to social media (SM) worldwide, according to Statista: a global data platform [1]. Nowadays, social media has become the main source of information and communication for people. It has promoted society towards a brand new ‘revolution.’ Contemporaneously, more and more mental health problems are being diagnosed, which seems to be attributed to the booming social media. This study thus investigated whether the duration of social media use negatively impacts stress, anxiety, and depression through meta-analysis. It achieves comprehensive research under the multicultural background, which has not been performed before this study. Method: A systematic review of the journal article and meta-analysis was conducted to examine the effectiveness of using the PubMed and PsycINFO on social media works on the mental health problem. Journal articles were eligible for inclusion if it was written in English and published before January 2011. Results: Retrieved Studies show the solid negative association of time spent on SM with a mental health problem. Conclusion and Limitation: This review provides effective evidence for the negative impact of using social media on psychological issues such as stress and anxiety. However, covered studies excluded unpublished studies and the lack of control about age and gender-related variables underline the obligation for further research.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126903614","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}

{"title":"Early-Warning of Peri-operative Critical Event Based on Multimodal Information Fusion","authors":"Yuwen Chen, Yu-jie Li, Wei Huang, Ju Zhang, Bin Yi, Xiaolin Qin","doi":"10.1145/3484377.3484389","DOIUrl":"https://doi.org/10.1145/3484377.3484389","url":null,"abstract":"The occurrence of perioperative critical adverse events will affect the quality of medical services and threaten the safety of patients. Using scientific methods to assess the risk of critical illness in perioperative period is of great significance to improve the quality of medical service and ensure the safety of patients. However, the diagnosis and treatment data of perioperative patients are multi-source and irregular, and only one physiological information can not accurately reflect the patient's condition. In previous studies, it is found that a variety of physiological information can transmit the information of human health or not, which can be used to evaluate critical illness and physical condition. Therefore, this paper integrates the preoperative clinical structure data, intraoperative vital signs monitoring time series data and intraoperative anesthesia event time series data. Based on deep learning technology, the multi-modal data of patients are embedded and mapped into the same recessive semantic space to realize the real-time tracking and early warning of severe events, reduce postoperative complications and improve the early diagnosis efficiency of critical adverse events. The results showed that the performance of the model based on the multi-modal data was better than that based on the real military data.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129359882","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}

{"title":"Transcriptional Differences in Luminal Epithelial Cells in Patients with and without Lymph Node Involvement in TNBC","authors":"Xiao Xu, Xinhe Zheng","doi":"10.1145/3484377.3484391","DOIUrl":"https://doi.org/10.1145/3484377.3484391","url":null,"abstract":"TNBC is an aggressive subtype of breast case which is hard to treat due to the high degree of heterogeneity and higher frequency of metastasis. Luminal progenitor cells (LPs) were previously suggested to play a role in the metastasis in TNBC. In this study, we use a publicly available scRNA-Seq dataset (GSE118389) to address the differences in transcriptional signatures of LPs and luminal epithelial cells in TNBC patients with and without lymph node involvement. When comparing the expression level of genes, we found there is a obvious difference in luminal epithelial cells between TNBC patients with and without lymph node involvement.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115187070","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}

{"title":"Association between Smartphone Addiction and Mental Health during the COVID-19 Pandemic 2021 among Inner Mongolia Medical University Students, China","authors":"Longlong Zhao, Nuchanad Hounnaklang","doi":"10.1145/3484377.3487040","DOIUrl":"https://doi.org/10.1145/3484377.3487040","url":null,"abstract":"Objective: The purpose of this study was to understand the status of smartphone addiction and mental health of Undergraduates in Inner Mongolia Medical University during the period of the prevalence of COVID-19, and to explore the relationship between the mental health status and smartphone addiction of Undergraduates in Inner Mongolia Medical University. Methodology: Five colleges were randomly selected from Inner Mongolia Medical University, and 100 undergraduate students were randomly selected from each college. A total of 500 students were investigated by questionnaire, including demographic characteristics, smartphone use behaviors, smartphone addition scale: Short Version (SAS-SV) (10 questions), life experience during COVID-19, Depression Anxiety Stress Scales (DASS-21) 21 questions. Univariate logistic regression analysis used binary logistical regression to explore the nature and significance of the relationship between dependent and independent variables. After putting the significant factors into multivariable logistic regression models to control any possible confounding factors, the factors significantly related to smartphone addiction and depression, anxiety, stress were proposed. Results: In the questionnaire survey (33.6% of males and 66.4% of females), the age range was 18 to 28 years old. Almost 277(55.4%) participants can be considered as smartphone addiction,233(44.6%) participants cannot be considered smartphone addiction.105 (21.0%) considered having depression, 153 (30.6%) had anxiety and 69 (13.8%) had stress. Smartphone addiction (OR=4.53), compared with non-addiction, addiction has a positive correlation with the depression the depression risk of smartphone addicts is 4.53 times that of non-smartphone addicts. smartphone addiction (OR=6.47), compared with non-addiction, addiction has a positive correlation with the anxiety the anxiety risk of smartphone addicts is 6.47 times that of non-smartphone addicts. Smartphone addiction (OR=4.05), compared with non-addiction, addiction has a positive correlation with the stress the stress risk of smartphone addicts is 4.05 times that of non-smartphone addicts. Conclusion: Smartphone addiction is very common among the undergraduates of Inner Mongolia Medical University. This study also determined the association between smartphone addiction and mental health of the undergraduates of Inner Mongolia Medical University. These results indicate that intervention measures need to be taken to reduce the smartphone addiction of Undergraduates of Inner Mongolia Medical University to improve their mental health.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124287074","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}

{"title":"Localization of the Epileptic Focus using Multi-scale Deep Learning","authors":"Rui Zhang, Yongjin Tang, Rui Yan, T. Cai, Hao Xu","doi":"10.1145/3484377.3484380","DOIUrl":"https://doi.org/10.1145/3484377.3484380","url":null,"abstract":"PET imaging is considered as one of safest and most significant methods for localizing the epileptic focus in the field of brain neuroscience. With the advent of the era of Artificial Intelligence, it becomes one of hot research topic that neurologist and radiologist are assisted to locate the epileptic focus by using Computer-aided Diagnosis method. In this study, we propose a novel method for localization of epileptic focus in PET imaging using Multi-scale Deep Learning method. Firstly, three different Mask Region-based Convolutional Neural Network models were used to extract the candidate of epileptic focus. The three models were produced by transferring learning towards Mask R-CNN utilizing training images that made up of PET scanning from three different scales. Each training image set contained 375 brain PET axial slices of epilepsy. Then three Deep Learning models were combined using the ensemble learning to reduce false positive results and to localize the epileptic focus. 48 PET axial slices were utilized as test set for this research. The sensitivity and specificity of this new method were 0.80 and 0.8125 respectively. The experimental results show the effectiveness of this method in locating epileptic focus.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131168312","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}

{"title":"Study on Named Entity Recognition in Chinese Literatures on Hypertension treatment","authors":"Jing Wang","doi":"10.1145/3484377.3484390","DOIUrl":"https://doi.org/10.1145/3484377.3484390","url":null,"abstract":"Chinese Medical literature research results are more accurate and representative than other medical texts. This paper studies the extraction method of named entity recognition in Chinese medical literatures on hypertension treatment. This paper proposes a Bi-directional Long Short-Term Memory-Conditional Random Fields (BiLSTM-CRF) model based on Attention mechanism for Chinese named entity recognition. BiLSTM-CRF is used as the model infrastructure while the Attention mechanism is used to learn the dependence of each word on the full text. In addition, the dictionary of literature keywords is built to improve the efficiency of recognition. Compared with the routine BiLSTM-CRF model, the recognition effect of the BILSTM-CRF model based on Attention mechanism was better. The value of Precision, Recall and F1 score were 84.6%, 87.9% and 86.2% respectively. The BiLSTM-CRF model based on Attention mechanism can effectively realize named entity recognition in Chinese medical literatures on hypertension treatment.","PeriodicalId":123184,"journal":{"name":"Proceedings of the 2021 International Conference on Intelligent Medicine and Health","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130870151","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}