2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)最新文献_第2页

Application of Intelligent Medical Self-Test Management 智能医疗自检管理的应用

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218467

Chein-Ting Chen, Sheng-Huang Kuo

引用次数: 0

Deep Learning-Assisted Lung Cancer Diagnosis from Histopathology Images 基于组织病理学图像的深度学习辅助肺癌诊断

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218594

Chun-Cheng Peng, Jiawei Wu

{"title":"Deep Learning-Assisted Lung Cancer Diagnosis from Histopathology Images","authors":"Chun-Cheng Peng, Jiawei Wu","doi":"10.1109/ECBIOS57802.2023.10218594","DOIUrl":"https://doi.org/10.1109/ECBIOS57802.2023.10218594","url":null,"abstract":"Early detection plays a critical role in enhancing patient survival rates as lung cancer continues to pose a significant global health challenge and remains one of the primary contributors to cancer-related mortality. Deep learning techniques are promising as they assist doctors in disease diagnosis, especially in medical imaging. In this research, we employed a dataset comprising histopathology images of lung cancer and colon cancer from Kaggle. The data encompassed five distinct categories of the tissues of the lung and colon. To classify the images, we used a deep learning methodology that leveraged the pre-trained neural network known as AlexNet. After fine-tuning the proposed model by substituting the last fully-connected layer, we optimized the parameters using the SGDM optimizer. As a result, the overall accuracy of the method reached 99.46%. Across all considered categories, the lung benign group performed best with 100% in terms of accuracy. The overall accuracy of this research surpassed that of three previously published journal papers and six conference papers, effectively proving the remarkable capability of deep learning in accurately classifying lung cancer images. In conclusion, this research result underscores the potential of deep learning in supporting medical professionals to diagnose lung cancer.","PeriodicalId":334600,"journal":{"name":"2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131246712","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

Acquisition and Remote Transfer of Operative Field View During Open Surgery 开放手术中手术视野的获取和远程转移

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218549

Malek Anabtawi, Jhasketan Padhan, A. Al-Ansari, Zhigang Deng, Elias Yaacoub, A. Mohammed, N. Navkar

引用次数: 0

A Design of Emote Education Platform for Traditional Chinese Medicine Pharmacology Based on VR Technology 基于VR技术的中医药药理学远程教学平台设计

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218433

Chuying Wang, Yajie Zhang, Lijing Li, Yumei Li

引用次数: 0

Copyright Page 版权页

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ecbios57802.2023.10218380

引用次数: 0

Facial Image Emotion Recognition Based on Convolutional Neural Networks and Haar Classifiers 基于卷积神经网络和Haar分类器的面部图像情感识别

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218544

J. Yeh, Wei-Tse Hung, Chia-Chen Chang, Ting-Hao Wang

{"title":"Facial Image Emotion Recognition Based on Convolutional Neural Networks and Haar Classifiers","authors":"J. Yeh, Wei-Tse Hung, Chia-Chen Chang, Ting-Hao Wang","doi":"10.1109/ECBIOS57802.2023.10218544","DOIUrl":"https://doi.org/10.1109/ECBIOS57802.2023.10218544","url":null,"abstract":"Facial expression shows the richest human expression and mainly conveys emotions and social signals. In recent years, the development of artificial intelligence technology and sufficient data have broken through previous limitations, opening up the development of intelligent emotion recognition. In this study, emotion recognition is conducted by a deep learning model with multiple layers to describe global features of facial emotions with facial images as input data and neural networks to learn facial features such as eyebrows, eyes, and mouth. The proposed model objectively and quickly presents emotional results, making it applicable to customer service feedback, judgment basis for medical personnel, fatigue driving detection, and more. The model uses facial images as input into a Haar classifier to remove the background of the image and focus on capturing the facial region. Based on the Convolution Neural Network (CNN) and the FER-2013 (Facial Expression Recognition 2013) test dataset. After the user inputs the facial image, the system's prediction accuracy increased by 7.83% compared to the baseline system, effectively improving the accuracy of facial emotion recognition.","PeriodicalId":334600,"journal":{"name":"2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116215114","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

Use of Nonlinear Analysis Methods for Evaluating IMU Data of Bilateral Jump Landing Tasks 应用非线性分析方法评价双侧跳降任务IMU数据

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218375

J. Hejda, T. Sugiarto, P. Volf, Yi-Jia Lin, P. Kutílek, W. Hsu, Marek Sokol, Jia-Lin Wu, Lýdie Leová, Yah-Shiun Jiang, Yong-Jie Deng

{"title":"Use of Nonlinear Analysis Methods for Evaluating IMU Data of Bilateral Jump Landing Tasks","authors":"J. Hejda, T. Sugiarto, P. Volf, Yi-Jia Lin, P. Kutílek, W. Hsu, Marek Sokol, Jia-Lin Wu, Lýdie Leová, Yah-Shiun Jiang, Yong-Jie Deng","doi":"10.1109/ECBIOS57802.2023.10218375","DOIUrl":"https://doi.org/10.1109/ECBIOS57802.2023.10218375","url":null,"abstract":"The use of nonlinear analysis methods provides new information when evaluating linear acceleration and angular velocity from a system with Inertial Measurement Unit (IMU) recording. This information is used as additional input to improve the estimation of the angular displacements in a neural network model. The measurements were performed on 24 participants (18 males and 6 females of an average age of $22.6pm 2.6$ years old, average height of $172.6pm 10.3$ cm, and an average weight of $72.2pm 16.02 text{kg})$ during bilateral jump landing tasks. In order to assess the differences between IMU estimated angle and the gold standard, data obtained from Qualysis optical Mocap (Qualisys AB, Göteborg, Sweden) and Delsys inertial measurement systems (Delsys Inc., Boston, MA, USA) were used for measurements during bilateral jump landing tasks. A total of 8 IMU sensors were placed on the sternum, L5, bilateral thighs, shanks, and foot. The thigh and shank sensors were placed on the middle of each thigh and shank along the anterior-posterior axis (middle thigh and middle shank) while the foot sensors were placed on the dorsal surface of the foot. Thirty retroreflective markers were placed on the pelvis and bilateral thigh, shanks, and foot to form a 7-linkage lower extremity model. Static calibration on each of the participants was performed during standing with anatomical position to define the neutral joint angle at bilateral hip, knee, and ankle. For quantification purposes, the Hurst exponent, Lyapunov exponent, approximate entropy, and multiscale sample entropy were used. The results suggest that when evaluating the placement of IMU on the shank and thigh to determine the knee angle, the Hurst exponent is capable of best distinguishing individual axes based on linear acceleration and angular velocity.","PeriodicalId":334600,"journal":{"name":"2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126941300","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

Detection of Bradycardia in Preterm Infants by Using ECG and Respiratory Signals 利用心电图和呼吸信号检测早产儿心动过缓

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218577

Ting-Kai Hsu, Hangzhang Cheng, S. Yao

引用次数: 0

Prediction of Retina Damage in Optical Coherence Tomography Image Using Xception Architecture Model 利用异常结构模型预测光学相干层析成像视网膜损伤

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218586

Minh Thanh Do, Hoang Nhut Huynh, Trung Nghia Tran, T. Hoang

{"title":"Prediction of Retina Damage in Optical Coherence Tomography Image Using Xception Architecture Model","authors":"Minh Thanh Do, Hoang Nhut Huynh, Trung Nghia Tran, T. Hoang","doi":"10.1109/ECBIOS57802.2023.10218586","DOIUrl":"https://doi.org/10.1109/ECBIOS57802.2023.10218586","url":null,"abstract":"One of the most vital human organs is the retina. Most of the data is gathered via our eyesight. Thus, maintaining good eye health is crucial for happy and healthy life and eyes. Unfortunately, hazardous eye conditions, including choroidal neovascularization (CNV), Drusen, and diabetic macular edema (DME), directly harm the retina. They are typically discovered late, making it frequently impossible to cure and restore vision. Significant vision loss or even complete blindness may result from this. Ophthalmologists can view the inner structure of the retina using the sophisticated medical imaging technology known as noninvasive retinal optical coherent tomography (OCT), which relies on the visual reflection of the tissues inside the eye. However, in practice, errors continue to occur in diagnosing illnesses in general and eye ailments in particular. Thus, we develop a deep learning model to help physicians diagnose CNV, Drusen, and DME more correctly and lessen medical examination and treatment mistakes. About 8,000 images from the Large Dataset of Labeled Optical Coherence Tomography (OCT) Images were used to train with the Xception's architecture model. The result of this classification study for three types of DME, CNV, and Drusen diseases showed an accuracy of 93%.","PeriodicalId":334600,"journal":{"name":"2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126745521","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

Unleashing Potential of Employees through Artificial Intelligence 通过人工智能释放员工的潜力

2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) Pub Date : 2023-06-02 DOI: 10.1109/ECBIOS57802.2023.10218636

Aishwarya Gowda A G, Hui-Kai Su, W. Kuo

引用次数: 0