Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences最新文献_第8页

Prediction of intermediate and high risk factors based on MRI imaging radiomics before neoadjuvant therapy for cervical cancer 宫颈癌新辅助治疗前基于MRI影像放射组学的中高危因素预测

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570868

Yimin Zhou, Rongrong Wu, Guoping Zuo, P. Bai

{"title":"Prediction of intermediate and high risk factors based on MRI imaging radiomics before neoadjuvant therapy for cervical cancer","authors":"Yimin Zhou, Rongrong Wu, Guoping Zuo, P. Bai","doi":"10.1145/3570773.3570868","DOIUrl":"https://doi.org/10.1145/3570773.3570868","url":null,"abstract":"Objective: A fusion model based on axial LAVA+C sequence images and clinical characteristics on preoperative MRI before neoadjuvant therapy is discussed for identifying intermediate and high risk factors in cervical cancer patients. Methods: In a retrospective analysis of 145 cervical cancer patients treated at Fujian Cancer Hospital between January 2013 and July 2018, cases with more than two intermediate risk factors or more than one high-risk factor were classified as positive based on pathological findings, while cases with fewer than two intermediate risk factors and no high-risk factors were classified as negative based on pathological findings. Using an entirely random process, the cases were split into 116 cases for the training set and 29 cases for the test set, based on the Ax-LAVA+C sequence to extract radiomics features. dimensionality reduction for features LASSO and spearman correlation coefficient are used to select the most advantageous radiomics features. The best radiomics models may be filtered out using seven machine learning techniques. To create a composite radiomics model, combine the imaging radiomics model and the clinical model. And assess the model's effectiveness using the ROC, decision curves, and calibration curves. Results: The AUC of the validation set in the clinical- radiomics model was 0.823, the accuracy was 0.793, the sensitivity was 0.667, and the specificity was 0.972, which were higher than the clinical model and comparable to the radiomics model. Conclusion: Before beginning neoadjuvant therapy, the MRI radiomics model based on the Ax-LAVA+C sequence is effective in identifying intermediate- and high-risk variables for postoperative cervical cancer.","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":"132019734","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

SCAR U-Net: A 3D Spatial-Channel Attention ResU-Net for Brain Tumor Segmentation SCAR U-Net:一种用于脑肿瘤分割的三维空间通道注意力网络

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570826

Mengxian Chi, Hong An, Xu Jin, Ke Wen, Zhenguo Nie

引用次数: 0

Path Planning Algorithms for Mobile Robots in Hospital Environment during Covid-19 新型冠状病毒肺炎期间医院环境下移动机器人路径规划算法

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570853

Weiyi He, Zebin Cao, Haiyi Ye

{"title":"Path Planning Algorithms for Mobile Robots in Hospital Environment during Covid-19","authors":"Weiyi He, Zebin Cao, Haiyi Ye","doi":"10.1145/3570773.3570853","DOIUrl":"https://doi.org/10.1145/3570773.3570853","url":null,"abstract":"Since 2019, the COVID-19 virus has spread worldwide, posing a significant health and safety concern. The application of mobile robots in the medical field has gradually demonstrated their unique advantages. Therefore, we focus on the application of mobile robots inwards. By collating and summarizing some of the most popular existing path planning algorithms, this paper illustrates that different algorithms can produce varying outcomes depending on different environments and hardware used. MATLAB is used in this study to simulate four algorithms: To determine the most efficient path, A*, RRT, RRT*, and PRM in a specific hospital map are compared, as well as parameters including path length, average execution time, and resource consumption. Modelling a single-layer hospital map makes it possible for mobile robots in the medical field to execute tasks more efficiently between entry and ward in the COVID-19 hospital environment. Based on a comparison and comprehensive consideration of the data derived from the simulations, it is found that the A* algorithm is superior in terms of optimality, completeness, time complexity, and spatial complexity. Therefore, the A* algorithm is more valuable in finding the best path for a mobile robot in a hospital environment.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"20 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":"124876747","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

Construction and Analysis of a Data-Driven T2-SMOTE-GBDT Prediction Model for Vascular Vertigo 血管性眩晕数据驱动的T2-SMOTE-GBDT预测模型的构建与分析

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570795

Dengqin Song, Tongqiang Yi, Hongci Chen, Xiong Zhang, Huiyun Pu, Shuangli Peng

引用次数: 0

Research on abnormal behavior recognition of the elderly based on spatial-temporal feature fusion 基于时空特征融合的老年人异常行为识别研究

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570823

Yulong He, Hanming Huang, Yezheng Wu, Guanglei Zhu

{"title":"Research on abnormal behavior recognition of the elderly based on spatial-temporal feature fusion","authors":"Yulong He, Hanming Huang, Yezheng Wu, Guanglei Zhu","doi":"10.1145/3570773.3570823","DOIUrl":"https://doi.org/10.1145/3570773.3570823","url":null,"abstract":"With the deepening of the aging society, the health care of the elderly and disabled people has been widely concerned by society. It is of great practical significance to monitor the physical conditions and abnormal behaviors of elderly and disabled people based on sensor devices to prevent diseases and dangerous behaviors. However, most of the current algorithms (classical machine learning algorithms, CNN, RNN, LSTM) are only limited to the traditional Euclidean space, with little expansion in Non-Euclidean space. The translation invariance limits the expression ability of spatial data. The signals collected by the wearable sensor based on human abnormal behavior recognition often come from different parts and different directions of the human body. The traditional Euclidean algorithm is used to solve the problem, which makes the classification results easy to ignore the spatial characteristics of the sensor signals. The emergence of graph neural networks provides a new method to solve this problem. A large number of studies have proved that the graph neural network has a great role in dealing with Non-Euclidean space problems. Therefore, this paper proposes a new method for abnormal behavior recognition of the elderly based on spatiotemporal feature fusion (SCGAT). The Non-Euclidean spatial features of sensor signals are extracted by graph attention neural network, and the classification model is constructed by combining the extracted time domain features of the time-series coding network. In the experimental results, the proposed method achieves better classification results than most of the current algorithms.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"20 25-26 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":"116724973","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 Artificial Intelligence in Drug Detoxification 人工智能在戒毒中的应用

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570860

Hanchen Shao, Zhencai Chen

引用次数: 0

Improved Deeplabv3+ based ultrasound image segmentation algorithm for thyroid nodules 基于Deeplabv3+的甲状腺结节超声图像分割改进算法

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570817

Mengze Gao, Li Yu, He Min

{"title":"Improved Deeplabv3+ based ultrasound image segmentation algorithm for thyroid nodules","authors":"Mengze Gao, Li Yu, He Min","doi":"10.1145/3570773.3570817","DOIUrl":"https://doi.org/10.1145/3570773.3570817","url":null,"abstract":"The incidence of thyroid nodules is increasing year by year, and ultrasonic detection is an effective means of thyroid nodule lesions, but the background of ultrasound images is chaotic, and the lesion area is similar to the background. The traditional segmentation algorithm produces a large number of invalid feature channels in the stage of encoding feature extraction, and the network continuously downsamples and pooling operations make the detail information of the thyroid nodule edge under the ultrasound image lose the detail information and the malignant nodule edge segmentation effect is not good. In view of the above problems, this paper proposes a thyroid nodule ultrasound image segmentation algorithm based on improved Deeplabv3+, which integrates the attention mechanism on the original Deeplabv3+ network structure, and designs a new attention mechanism module ES-Net, which adds a spatial attention module on the basis of ECA-Net channel attention, which can effectively pay attention to the spatial structure under the ultrasound image. Experimental data show that in the public dataset of thyroid ultrasound images, the Dice loss decreased from 0.192 to 0.120, and the IoU (Intersection of Union) increased from 87.80% to 89.62%. The results show that the improved Deeplabv3+ attention model has a 1.82% accuracy improvement in the segmentation of ultrasound images of thyroid nodules, which verifies the effectiveness of the algorithm.","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":"129535500","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

Study on the optimization of emergency medical staff regional dispatch considering the ratio of doctors and nurses 考虑医护比例的急诊医务人员区域调度优化研究

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570827

Li Luo, Yiting Luo, Yuyu Geng, Xiang Li, Yuan-cheng Fang, Yipeng Yang

{"title":"Study on the optimization of emergency medical staff regional dispatch considering the ratio of doctors and nurses","authors":"Li Luo, Yiting Luo, Yuyu Geng, Xiang Li, Yuan-cheng Fang, Yipeng Yang","doi":"10.1145/3570773.3570827","DOIUrl":"https://doi.org/10.1145/3570773.3570827","url":null,"abstract":"Public health emergencies will pose an enormous challenge to healthcare service systems. As COVID-19 rage across the globe, we realize that COVID-19 exposes the problem of inadequate research on the dispatch of emergency medical personnel in response to a major epidemic outbreak. In the face of major public health emergencies, failure in timely satisfaction of healthcare demands by local healthcare professionals necessitates human resource support from other regions. To address this issue, further research is needed to gain better insights into interregional emergency human resource allocation. This paper aims to offer attention to patients’ medical needs and suppose that there are support hubs outside the outbreak region offering an external supply of medical personnel. The hospitals in these support hubs are categorized based on variables such as capacity, medical capability, and the number of dispatched personnel per day. An interregional emergency allocation model was established to consider the proper doctor-patient ratio and nurse-patient ratio in emergency response using methods such as mathematical programming. And relevant management suggestions were then offered via analysis. Research in this paper provides allocation models and proposals that healthcare professionals can refer to when making resource allocation decisions in emergency response.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"63 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":"129833544","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 Value of Brain-Computer Interface in Stroke Upper Rehabilitation 脑机接口在脑卒中上肢康复中的应用价值

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570822

Jonathan Shang-Hong Ji

{"title":"The Value of Brain-Computer Interface in Stroke Upper Rehabilitation","authors":"Jonathan Shang-Hong Ji","doi":"10.1145/3570773.3570822","DOIUrl":"https://doi.org/10.1145/3570773.3570822","url":null,"abstract":"Stroke is a leading cause of acquired disability that can result in distal upper extremity functional motor impairments. As stroke mortality rates decrease due to advancements in medicine, there has been an increased number of disabled individuals. In recent years, brain-computer interface (BCI) based therapy has shown promising results for meeting the demands of rehabilitating the increasing amount of post-stroke patients. However, BCI has developed primarily in bottom-up, exercising-based intervention models which limits its potential application to patients with extreme disabilities. By stimulating upper body motor function, in which case can restore neural plasticity and motor function, BCI with motor feedback can help us discuss the importance of BCIs usage in top-down intervention. In this paper, we give a brief introduction to stroke upper rehabilitation technologies and the shortcomings of conventional treatment by discussing contemporary BCI systems and three main different types of technologies in signal acquisition. We conclude from a table of robotic EEG-based BCI system studies that treatment should be personalized for stroke patients who need upper limb rehabilitation. By utilizing BCI's customizability in signal acquisition technologies, there can be dozens of different possibilities for developing new novel top-down models.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"25 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":"128321198","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

Introduce and Recommend Medications to Facilitate Sexual Intercourse—Testosterone and Sildenafil 介绍和推荐促进性交的药物——睾酮和西地那非

Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences Pub Date : 2022-10-13 DOI: 10.1145/3570773.3570820

Long-fei Tu

引用次数: 0