Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences最新文献_第10页

Correlation Study of MRI Area of Lumbar Disc Degeneration with Pfirrmann Grading 腰椎间盘退变MRI面积与Pfirrmann分级的相关性研究

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570852

Zunhai Gao, Hongtao Gao, Yuzhan Qiu

{"title":"Correlation Study of MRI Area of Lumbar Disc Degeneration with Pfirrmann Grading","authors":"Zunhai Gao, Hongtao Gao, Yuzhan Qiu","doi":"10.1145/3570773.3570852","DOIUrl":"https://doi.org/10.1145/3570773.3570852","url":null,"abstract":"The correlation between the modified Pfirrmann grading and the MRI area of lumbar disc degeneration is investigated, which provide a quantitative method for the diagnostic grading of lumbar disc degeneration. MRI data of 60 cases with different degrees of lumbar disc degeneration are collected. Use the threshold segmentation technology to divide the target area in the MRI image, then calculate the segmentation threshold based on the image gray histogram, then segment the image according to the threshold, select the threshold by maximizing the interclass variance between, and then calculate the height of the intervertebral disc and the area of the intervertebral foramen in the MRI image. Combined with the doctor's diagnosis, the improved Pfirmann classification of 60 patients is obtained. According to the corresponding relationship between the intervertebral foramen area of MRI images and the modified Pfirrmann classification, the higher the modified pfirmann classification, the smaller the intervertebral foramen area of intervertebral discs. There is a certain correlation between the area of intervertebral foramen in MRI images and the modified Pfirmann classification. The area of lumbar intervertebral foramen in MRI images provides a quantitative method for the diagnosis and classification of lumbar disc degeneration.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129147467","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

MRIGAT: Many-to-many Recommendation using Interaction based Knowledge Graph Attention MRIGAT:使用基于交互的知识图注意力的多对多推荐

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570888

Feng Gao, Kai-yi Yuan, J. Gu, Yun Liu

{"title":"MRIGAT: Many-to-many Recommendation using Interaction based Knowledge Graph Attention","authors":"Feng Gao, Kai-yi Yuan, J. Gu, Yun Liu","doi":"10.1145/3570773.3570888","DOIUrl":"https://doi.org/10.1145/3570773.3570888","url":null,"abstract":"Recommendation systems combining Graph Neural Networks and Knowledge Graphs have been successfully applied in various domains. However, most existing approaches only consider one-to-one or one-to-many user-item interactions and cannot cater to many-to-many recommendation scenarios, such as providing prescriptions based on clinical diagnosis and medical history. Providing such a recommendation requires considering the implicit interaction within input user features as well as output candidates. In this paper, we propose a two-stage knowledge graph attention aggregation mechanism that helps recommend drug combinations for a patient based on his conditions. First, a disease-drug interaction graph is constructed and integrated with the medical domain knowledge, forming a collaborative knowledge graph. Secondly, an intra-feature attention aggregation is performed to obtain the representations of diseases and drugs based on drug-drug and disease-disease interactions, respectively. Thirdly, an inter-feature attention aggregation is performed using the disease-drug interaction to better represent a user's condition. Finally, the user's condition representation is concatenated with other user features to generate the final user representation for the prescription recommendation. Experiments with realistic datasets show that our approach can outperform existing recommendation systems by 4.3% and 6.1% in precision and recall, respectively.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127535607","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

Clinical performance evaluation of screw- and cement-retained implant restorations- An up to 10 year retrospective research 螺钉和骨水泥保留种植体修复体的临床性能评估-一项长达10年的回顾性研究

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570824

Ting Zhou, Jiranut Vuthiparum, Romrudee Kesa, B. Buranawat

{"title":"Clinical performance evaluation of screw- and cement-retained implant restorations- An up to 10 year retrospective research","authors":"Ting Zhou, Jiranut Vuthiparum, Romrudee Kesa, B. Buranawat","doi":"10.1145/3570773.3570824","DOIUrl":"https://doi.org/10.1145/3570773.3570824","url":null,"abstract":"Objectives: The aim of this study is to evaluate the clinical performance of two types of retained dental implant therapy on the basis of Implant Quality Scale. Materials and methods: Thirty-five patients with 41cement-retained and 38 screw-retained implant restorations were evaluated using parameters including pain/sensitivity on function, mobility, marginal bone loss (MBL), probing depth (PD), plaque index (PI), sulcus bleeding index (SBI), peri-implant inflammation. Results: No pain but one implant-retained restoration of each group showed mobility. Probing depth of cement -retained group was higher than that of screw-retained group(P<0.05). The average MBL with cement-retained and screw-retained restoration was 0.3571±0.5688 mm and 0.5395±0.78567mm, which was not significantly different between the two groups(P>0.05), yet 2 screw-retained crowns were detected with bone loss of 2-3mm. The results of plaque index, sulcus bleeding index and inflammation demonstrated that the cement-retained group accounted for a higher proportion when same score, or a higher incidence in the higher grade. There were significant positive Spearman correlations among Plaque index, sulcus bleeding index and peri-implant inflammation. Conclusion: Compared with the screw-retained group, the cement-retained group showed similar failure rates but higher success rates. However, excess cement and adaptation of porcelain materials could strengthen plaque accumulation hence resulting in more severe inflammatory performance in the cement-retained group.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131897201","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

The mechanism of amoxicillin and azithromycin to treat acute tonsillitis 阿莫西林和阿奇霉素治疗急性扁桃体炎的作用机制

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570787

Meng-Ying Hu

引用次数: 0

Downregulation the expression of miR-181 promotes RAS-mutated thyroid cancer apoptosis by activating the RASSF1A expression using Intelligent Medical Instruments and Medical Robots 通过智能医疗仪器和医疗机器人激活RASSF1A表达，下调miR-181表达促进ras突变的甲状腺癌凋亡

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570776

Xiaobing Ye

{"title":"Downregulation the expression of miR-181 promotes RAS-mutated thyroid cancer apoptosis by activating the RASSF1A expression using Intelligent Medical Instruments and Medical Robots","authors":"Xiaobing Ye","doi":"10.1145/3570773.3570776","DOIUrl":"https://doi.org/10.1145/3570773.3570776","url":null,"abstract":"Purpose: This paper investigated the mechanism of downregulation of miR181 in papillary thyroid cancer (PTC) tumor cells to activate the expression of RASSF1A protein thus promoting the apoptosis of tumor cells. Methods: The expression of miR-181 was tested by real-time polymerase chain reaction (RT-PCR). Flow Cytometry (FACS) was used to determine the apoptosis ratio of cancer cells respectively. It was detected by Western blot that the RASSF1A protein expression was regulated by miR-181 in PTC cells. Xenograft mouse model is used to measure the change of tumor volume. Possible Results: The possible results are: Downregulation of miR181 activated RASSF1A expression and thus promotes the apoptosis of tumor cells; Downregulation of miR181 only activated RASSF1A expression but did not promote the apoptosis of tumor cells; Downregulation of miR181 neither activated RASSF1A expression nor promotes the apoptosis of tumor cells. Conclusion: Our experiment investigated the activation of the suppressed basal tumor suppressor gene RASSF1A targeting thyroid cancer with miR181 as a regulator. Future studies can focus on finding more small molecules that regulate RASSF1 and the mechanism of action of the RASSF1 gene to explore the method of targeted therapy for other cancers caused by RAS mutations, including thyroid cancer.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133795103","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

Fine-Grained Gastrointestinal Endoscopy Image Categorization 细粒度胃肠道内镜图像分类

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570836

Peng Xiao, Pan Gou, Bin Wang, Erqiang Deng, Pengbiao Zhao

引用次数: 0

Loss Optimization Based Algorithm for Multi-classification of ECG Signal 基于损失优化的心电信号多重分类算法

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570856

Junhui Liu, Ming Zeng, Ke Shan, Lan Tian

{"title":"Loss Optimization Based Algorithm for Multi-classification of ECG Signal","authors":"Junhui Liu, Ming Zeng, Ke Shan, Lan Tian","doi":"10.1145/3570773.3570856","DOIUrl":"https://doi.org/10.1145/3570773.3570856","url":null,"abstract":"There is a wide range of cardiac diseases, and the electrocardiogram (ECG) signal allows for relevant diagnostic classification. With the development of telemedicine and computer-aided diagnostic techniques, early detection and timely treatment place new demands on diagnostic algorithms. In this paper, we propose a deep learning algorithm for ECG signal multi-classification based on loss optimization, the decomposing multi-classification task of ECG signals into multiple ECG signals binary classification tasks, using the framework of a multi-task deep learning algorithm by sharing task features, and performing loss optimization in terms of both magnitude and direction of task gradients to avoid manual setting of task loss weights and negative migration due to task losses canceling each other out, thereby improving the performance of the ECG signal multi-classification task. We evaluated the proposed algorithm using the PTB-XL dataset by decomposing the ECG signals 23 classification task into 23 binary classification tasks. The experimental results showed that the macro-averaging area under the curve achieved 0.950, the accuracy achieved 0.965, the label-based macro-averaging F1 score achieved 0.583 and the sample-based F1 score achieved 0.777. The proposed multi-task deep learning algorithm showed good performance in the multi-classification of ECG signal compared to the single-task learning algorithm.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123600935","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

AEMVC: anchor enhanced multi-omics cancer subtype identification AEMVC:锚定增强多组学癌症亚型鉴定

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570802

Nan Zhou, Shunfang Wang, Zhuokun Tan

引用次数: 1

Mycotoxin OTA Triggers Alzheimer's Disease 真菌毒素OTA引发阿尔茨海默病

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570835

Zhiheng Zhang

引用次数: 0

IDO level increase in Kynurenine Pathway Contributes to the Development of Alzheimer's Disease 犬尿氨酸通路IDO水平升高与阿尔茨海默病的发展有关

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570797

Ziyu Xue, Yiran Yang, Borui Li, Wenrui Li, Jiani Chen, Yue Pan

{"title":"IDO level increase in Kynurenine Pathway Contributes to the Development of Alzheimer's Disease","authors":"Ziyu Xue, Yiran Yang, Borui Li, Wenrui Li, Jiani Chen, Yue Pan","doi":"10.1145/3570773.3570797","DOIUrl":"https://doi.org/10.1145/3570773.3570797","url":null,"abstract":"Tryptophan is crucial to many functions of the body. Research has shown that its involvement in the Kynurenine pathway (KP) also plays a role in the development of various neurodegenerative diseases (ND). As one of the upstream enzymes in KP, Indoleamine 2,3-dioxygenase (IDO) controls the production of several critical downstream metabolites. Some of these metabolites, such as kynurenic acid (KYNA), possess neuroprotective properties, while some other, such as quinolinic acid (QUIN) are neurotoxic. Hence, the balance between these species is closely linked to the pathogenesis of NDs. Interesting, a positive association has also been found between the level of IDO and the level of amyloid peptide Aβ1-42 involved in Alzheimer's disease. Therefore, this experiment aims to investigate the mechanistic link between increases in levels of IDO and beta-amyloid production. We hypothesize that an increase in IDO level caused by systemic inflammation promotes the generation of key markers of AD by causing an imbalance in levels of tryptophan metabolites, specifically by shifting towards production of neurotoxic metabolite (QUIN) over neuroprotective species (KYNA).","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"9 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120851927","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