2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)最新文献_第3页

Federated Transfer Learning for Energy Efficient Privacy-preserving Medical Image Classification 基于联邦迁移学习的节能隐私医学图像分类

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982789

M. Ahmed, S. Giordano

{"title":"Federated Transfer Learning for Energy Efficient Privacy-preserving Medical Image Classification","authors":"M. Ahmed, S. Giordano","doi":"10.1109/HealthCom54947.2022.9982789","DOIUrl":"https://doi.org/10.1109/HealthCom54947.2022.9982789","url":null,"abstract":"The deep convolutional neural networks are widely used in medical image classification tasks. In some cases, they have outperformed physicians and achieved significant results. Unlike natural images, medical image dataset are very hard to collect, because they are protected by the privacy regulations to preserve patient's anonymity and requires a great deal of professional expertise to label them. However, because of the easier access and availability of high-performance computational resources, leveraging deep neural networks to detect diseases is becoming increasingly popular and common practice among healthcare researchers. As a result, considerable amount of energy is consumed to find an optimal and effective solution, which has a huge impact on our environment and contributes to global warming to some level.To address these challenges and reduce the carbon footprint caused by the deep learning practitioners, we attempted to combine the advantages of both federated learning and transfer learning for the medical image classification task in our study. Our findings suggest that federated transfer learning could be an useful technique to minimize computational costs and energy efficient, while maintaining privacy and addressing the problem of data scarcity. Moreover, this approach can be applied to solve other healthcare related tasks.","PeriodicalId":202664,"journal":{"name":"2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131988010","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

Cellular IoT based Secure Monitoring System for Smart Environments 基于蜂窝物联网的智能环境安全监控系统

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982776

K. Saleem, Faisal Yousef Alfariheedi, R. Ouni, J. Al-Muhtadi

{"title":"Cellular IoT based Secure Monitoring System for Smart Environments","authors":"K. Saleem, Faisal Yousef Alfariheedi, R. Ouni, J. Al-Muhtadi","doi":"10.1109/HealthCom54947.2022.9982776","DOIUrl":"https://doi.org/10.1109/HealthCom54947.2022.9982776","url":null,"abstract":"In this paper, a remote monitoring system enabled with the smart internet of things (IoT) station for ambient assisted living (AAL) and smart environments is introduced. IoT station that is based on Waspmote platform to work as an intelligent device for capturing the data and transfers through 3rd Generation (3G) cellular module to the cloud by avoiding redundancy. The complete architecture of the developed ubiquitous monitoring system for AAL is elaborated with the process flow. The video camera sensor board with a presence sensor is connected to the Waspmote to take a snapshot or a video clip when there is any movement in the surrounding. The IoT station with the sensor board have a capability to detect and take picture even in a dark environment. The Waspmote generate message as soon as the motion sensor is triggered and send the image to the storage server using file transfer protocol (FTP) or the file transfer protocol secure (FTPs) over cellular communication. The recent related work is reviewed and discussed to show the advantages of the proposed design. Furthermore, the real testbed experiment presents the efficiency of the cellular IoT based monitoring system.","PeriodicalId":202664,"journal":{"name":"2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127512754","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

Massive Open Online Course (MOOC) for the Detection and Intervention of Suicidal Risk Patients: Evaluation and Lessons Learned in times of Covid-19 发现和干预自杀风险患者的大规模在线开放课程:2019冠状病毒病时期的评估和经验教训

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982763

Gema Castillo-Sánchez, Isabel de la Torre, J. J. Rodrigues, Laura García Garcia, M. Franco-Martín

{"title":"Massive Open Online Course (MOOC) for the Detection and Intervention of Suicidal Risk Patients: Evaluation and Lessons Learned in times of Covid-19","authors":"Gema Castillo-Sánchez, Isabel de la Torre, J. J. Rodrigues, Laura García Garcia, M. Franco-Martín","doi":"10.1109/HealthCom54947.2022.9982763","DOIUrl":"https://doi.org/10.1109/HealthCom54947.2022.9982763","url":null,"abstract":"MOOCs can be used to provide specialized and continuing medical education in times of Covid-19. The procedure to evaluate the satisfaction of this MOOC aimed at primary care health professionals for the detection and management of suicidal risk had descriptive statistics, Cronbach's Alpha, and CHAID analysis (Chi-square Automatic Interaction Detector) to find the factor that most influenced the satisfaction of this course. This evaluation was complemented with thematic analysis. CHAID analysis of this MOOC course, the satisfaction of 53% Excellent was explained by the Course Content Assessment with a value of P <.001. The results of the thematic analysis were that 75% of the learning obtained corresponds to the general objective of the course. 53% of the most relevant topics of this MOOC were considered useful and of interest to their profession. Health professionals liked the final interview and the practical cases, they requested more real cases to better manage the risk of suicide. The achievement of the objective of this MOOC helps to contribute to the prevention of suicide. We can learn that this type of course is feasible at a technological level and that it requires a great commitment or interest from health professionals to carry it out satisfactorily in times of Covid-19.","PeriodicalId":202664,"journal":{"name":"2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115480941","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

An Industrial IoT-Based Ontology Development for Well-Being, Aging and Health: A Scoping Review 基于工业物联网的福祉、老龄化和健康本体开发:范围综述

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982769

H. Belani, P. Šolić, T. Perković

{"title":"An Industrial IoT-Based Ontology Development for Well-Being, Aging and Health: A Scoping Review","authors":"H. Belani, P. Šolić, T. Perković","doi":"10.1109/HealthCom54947.2022.9982769","DOIUrl":"https://doi.org/10.1109/HealthCom54947.2022.9982769","url":null,"abstract":"Well-being, aging and health is a multidimensional concept covering well-being, aging and health aspects of individuals, communities and ecosystems in the appropriate contexts. Various technology-enabled solutions can contribute to well-being, aging and health goals, and one of key trending technologies enabling digital transformation in healthcare and medicine is Internet of Things. This paper proposes an approach to industrial Internet of Things-based ontology development for well-being, aging and health, in order to structure the knowledge concepts needed for data acquisition and the overall system to contribute to well-being, aging and health. Given its multidisciplinary nature and the need to make use of semantic structures for data processing and usage in Internet of Things-based applications, this scoping review elaborates on usage of ontologies for implementation of Internet of Things solutions, aiming at extending the ontology of choice, reusing parts of existing ontologies and adding new constructs for cross-domain reasoning. In order to enable more efficient use of resources at the application level, an abstract layer of semantic middleware should reason on acquired data and allow for application business logic to trigger actuators while preserving safety and security.","PeriodicalId":202664,"journal":{"name":"2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122638718","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

SWeeT: Security Protocol for Wearables Embedded Devices’ Data Transmission SWeeT:可穿戴嵌入式设备数据传输安全协议

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982744

Mohammad Ebrahimabadi, Mohamed F. Younis, Wassila Lalouani, Abdulaziz Alshaeri, Naghmeh Karimi

引用次数: 0

Prediction of Hospital Status of COVID-19 Patients from E-Health Records 基于电子病历的COVID-19患者住院状况预测

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982738

W. Madill, Nguyen Duy Thong Jase Tran

{"title":"Prediction of Hospital Status of COVID-19 Patients from E-Health Records","authors":"W. Madill, Nguyen Duy Thong Jase Tran","doi":"10.1109/HealthCom54947.2022.9982738","DOIUrl":"https://doi.org/10.1109/HealthCom54947.2022.9982738","url":null,"abstract":"In the current era of big data, very large amounts of data are generating at a rapid rate from a wide variety of rich data sources. Embedded in these big data are valuable information and knowledge that can be discovered by data science, data mining and machine learning techniques. Electronic health (e-health) records are examples of the big data. With the technological advancements, more healthcare practice has gradually been supported by electronic processes and communication. This enables health informatics, in which computer science meets the healthcare sector to address healthcare and medical problems. As a concrete example, there have been more than 610 millions cumulative cases of coronavirus disease 2019 (COVID-19) worldwide over the past 2.5 years since COVID-19 has declared as a pandemic. As some of these cases require hospitalization. it is important to estimate the demand in hospitalization. Moreover, different levels of hospitalization may require different types of resources (e.g., hospital beds, medical staff). For example, patients admitted into the intensive care unit (ICU) may require assisted ventilation. Hence, in this paper, we present models to make predictions based on e-health records. Specifically, our binary model predicts whether a patient require hospitalization, whereas our multi-class model predicts what level of hospitalization (e.g., regular ward, semi-ICU, ICU) is required by the patient. Our models uses few-shot learning (and may use multi-task learning) with autoencoders (comprising encoders and decoders) and a predictor. Evaluation results on real-life e-health records show the practicality of our models in predicting hospital statuses of COVID-19 cases and the benefits of these models towards effective allocation of resources (e.g., hospital facilities, staff).","PeriodicalId":202664,"journal":{"name":"2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129004899","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

Impact of Using Soft Exposure Thresholds in Automatic Contact Tracing 使用软暴露阈值对自动接触追踪的影响

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982790

K. Sayrafian, Brian Cloteaux, V. Marbukh

{"title":"Impact of Using Soft Exposure Thresholds in Automatic Contact Tracing","authors":"K. Sayrafian, Brian Cloteaux, V. Marbukh","doi":"10.1109/HealthCom54947.2022.9982790","DOIUrl":"https://doi.org/10.1109/HealthCom54947.2022.9982790","url":null,"abstract":"Current automatic exposure notification apps primarily operate based on hard distance/time threshold guidelines (e.g., 2 m/15 min in the United States) to determine exposures due to close contacts. However, the possibility of virus transmission through inhalation for distances over the specified distance threshold might necessitate consideration of soft distance/time thresholds to accommodate all transmission scenarios. In this paper, using a simplifying approximation on the instantaneous rate of the viral exposure versus distance, we extend the definition of \"contact\" by proposing a soft distance/time threshold which includes the possibility of getting exposed at any distance (within certain limits) around an infected person. We then analyze the performance of automatic exposure notification with Bluetooth-based proximity detection by comparing the exposure results when soft or hard thresholds are used. This study is done through an agent-based simulation platform that allows for a comprehensive analysis using several system parameters. By tuning the parameters of the proposed soft thresholds, a more accurate determination of possible exposures at any distance would be possible. This would enhance the effectiveness of an automatic contact tracing system. Our results indicate the noticeable impact of using the soft distance/time threshold on the exposure detection accuracy.","PeriodicalId":202664,"journal":{"name":"2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124173509","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

Towards Explainability in mHealth Application for Mitigation of Forward Head Posture in Smartphone Users 在移动健康应用中缓解智能手机用户头部前倾姿势的可解释性

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982740

Richard O. Oyeleke, Babafemi G. Sorinolu

{"title":"Towards Explainability in mHealth Application for Mitigation of Forward Head Posture in Smartphone Users","authors":"Richard O. Oyeleke, Babafemi G. Sorinolu","doi":"10.1109/HealthCom54947.2022.9982740","DOIUrl":"https://doi.org/10.1109/HealthCom54947.2022.9982740","url":null,"abstract":"Machine learning (ML) algorithms have recorded tremendous successes in many areas, notably healthcare. With increasing computing power of mobile devices, mobile health (mHealth) applications are embedded with ML models to learn users behavior and influence positive lifestyle changes. Although ML algorithms have shown impressive predictive power over the years, nonetheless, it is necessary that their inferences and recommendations are also explainable. Explainability can promote users’ trust, particularly when ML algorithms are deployed in high-stake domains such as healthcare. In this study, first, we present our proposed situation-aware mobile application called Smarttens coach app that we developed to assist smartphone users in mitigating forward head posture. It embeds an efficientNet CNN model to predict forward head posture in smartphone users by analyzing head posture images of the users. Our Smarttens coach app achieved a state-of-the-art accuracy score of 0.99. However, accuracy score alone does not tell users the whole story about how Smarttens coach app draws its inference on predicted posture binary class. This lack of explanation to justify the predicted posture class label could negatively impact users’ trust in the efficacy of the app. Therefore, we further validated our Smarttens coach app posture prediction efficacy by leveraging an explainable AI (XAI) framework called LIME to generate visual explanations for users’ predicted head posture class label.","PeriodicalId":202664,"journal":{"name":"2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132414231","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

Analyze the Effect of Healthy Behavior on Weight Change and Its Conceptual Use in Digital Behavioral Intervention 分析健康行为对体重改变的影响及其在数字行为干预中的概念应用

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982785

Ayan Chatterjee, Nibedita Pahari, Martin W. Gerdes, Ram Bajpai

{"title":"Analyze the Effect of Healthy Behavior on Weight Change and Its Conceptual Use in Digital Behavioral Intervention","authors":"Ayan Chatterjee, Nibedita Pahari, Martin W. Gerdes, Ram Bajpai","doi":"10.1109/HealthCom54947.2022.9982785","DOIUrl":"https://doi.org/10.1109/HealthCom54947.2022.9982785","url":null,"abstract":"The gradual increase of negative behavior in humans because of physical inactivity, unhealthy habit, and improper nutrition expedites the growth of lifestyle diseases. Proper lifestyle management may help to reach personal weight goals or maintain a normal weight range with optimization of health behaviors (physical activity, diet, and habits). This study conceptualizes a method to integrate the proposed mathematical model in a digital intervention strategy targeting obesity as a study case. We verify our proposed model with simulated data and compare it with related models based on the defined constraints. We express the mathematical model as a function of activity, habit, and nutrition with the first order law of thermodynamics, basal metabolic rate (BMR), total daily energy expenditure (TDEE), and body-mass-index (BMI) to establish a link between health behavior and weight change. We have used revised Harris-Benedict formulas (HB) for BMR and TDEE calculations. The proposed model showed a strong relationship between health behavior and weight change. The adoption of BMR and TDEE measures following the revised HB formula has outperformed the classical Wishnofsky’s rule (3500 kcal. ≈ 1 lb. or 7700 kcal ≈ 1 Kg.), and the models proposed by Toumasis et al., Azzeh et al., and Mickens et al. with an average standard deviation (σ) of ±2.26, ±2.67, ±2.432, and ±2.29 respectively. This study helped us to understand the impact of healthy behavior on weight change with a mathematical model and its importance in maintaining a healthy lifestyle.","PeriodicalId":202664,"journal":{"name":"2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134174338","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

Experiments with bioradars in an automotive environment 生物雷达在汽车环境下的实验

2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) Pub Date : 2022-10-17 DOI: 10.1109/HealthCom54947.2022.9982759

Tiago Costa, Diana Carvalhais, A. Carvalho, P. Carvalhal, Victor Coelho, Paulo Cardoso

引用次数: 1