2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)最新文献

Improved Barrett's Cancer Detection in Volumetric Laser Endomicroscopy Scans Using Multiple-Frame Voting 采用多帧投票的体积激光显微内镜扫描改进巴雷特癌症检测

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-14 DOI: 10.1109/CBMS.2017.31

A. Rikos, F. V. D. Sommen, A. Swager, S. Zinger, E. Schoon, W. Curvers, J. Bergman, P. D. With

{"title":"Improved Barrett's Cancer Detection in Volumetric Laser Endomicroscopy Scans Using Multiple-Frame Voting","authors":"A. Rikos, F. V. D. Sommen, A. Swager, S. Zinger, E. Schoon, W. Curvers, J. Bergman, P. D. With","doi":"10.1109/CBMS.2017.31","DOIUrl":"https://doi.org/10.1109/CBMS.2017.31","url":null,"abstract":"This paper explores the feasibility of using multiframe analysis to increase the classification performance of machine learning methods for cancer detection in Volumetric Laser Endomicroscopy (VLE). VLE is a novel and promising modality for the detection of neoplasia in patients with Baretts Esophagus (BE). It produces hundreds of high-resolution, cross-sectional images of the esophagus and offers considerable advantages compared to current methods. While some recent studies have proposed cancer detection algorithms for single VLE frames, the study described in this paper is the first to make use of VLE volumes for the differentiation between dysplastic and non-dysplastic tissue. We explore the use of various voting schemes for a broad range of features and classification methods. Our results demonstrate that multi-frame analysis leads to superior performance, irrespective of the chosen feature-classifier combination. By using multi-frame analysis with straightforward voting methods, the Area Under the receiver operating Curve (AUC) is increased by an average of over 12% compared to using single VLE frames. When only considering methods that achieve expert performance or higher (AUC≥0.81), an even larger performance improvement of up to 16.9% is observed. Furthermore, with many feature/classifier combinations showing AUC values ranging from 0.90 to 0.98, our experiments indicate that computeraided methods can considerably outperform medical experts, who demonstrate an AUC of 0.81 using a recently proposed clinical prediction model.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126181961","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

HealthShare: Using Attribute-Based Encryption for Secure Data Sharing between Multiple Clouds HealthShare:在多云之间使用基于属性的加密实现安全的数据共享

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-13 DOI: 10.1109/CBMS.2017.30

A. Michalas, N. Weingarten

引用次数: 12

An Automatic EEG Based System for the Recognition of Math Anxiety 基于脑电图的数学焦虑自动识别系统

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-13 DOI: 10.1109/CBMS.2017.107

M. Klados, N. Pandria, A. Athanasiou, P. Bamidis

引用次数: 9

PhytoCloud: A Gamified Mobile Web Application to Modulate Diet and Physical Activity of Women with Breast Cancer 植物云:一个游戏化的移动网络应用程序，以调节乳腺癌妇女的饮食和身体活动

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-13 DOI: 10.1109/CBMS.2017.164

D. Economou, M. Dwek, Claire Roberston, Bradley Elliott, Thanos Kounenis, T. Azimi, M. Ramezanian, Nathan Bell

{"title":"PhytoCloud: A Gamified Mobile Web Application to Modulate Diet and Physical Activity of Women with Breast Cancer","authors":"D. Economou, M. Dwek, Claire Roberston, Bradley Elliott, Thanos Kounenis, T. Azimi, M. Ramezanian, Nathan Bell","doi":"10.1109/CBMS.2017.164","DOIUrl":"https://doi.org/10.1109/CBMS.2017.164","url":null,"abstract":"Breast cancer incidence and mortality rates vary geographically reflecting factors including regional and cultural differences in diet and lifestyle. There are numerous successful commercial mobile apps to help people control their diet and manage weight. However, such products are not suitable for people with special medical conditions that may require targeted dietary as well as motivational support. The paper presents a user centered approach of developing a Mobile Web App that focuses on breast cancer patients looking at their specific dietary, physical and mental requirements depending on the stage of their medical treatment. The paper explores the effect of incorporating gamification and social media as motivational drive to engage and motivate people to achieve their goals of adopting healthier eating habits while increasing physical activity in order ensure lasting lifestyle behavioural change. The design of PhytoCloud is being described, a gamified Mobile Web App that enables users to record their dietary habits and physical activity and motivate their consumption of food with oestrogen-like properties (phytoestrogens) which are linked to the prevention of reappearance of breast cancer. The paper concludes with a discussion of future directions and adaptations to the current design to suite a Mobile Native Application design.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121907185","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: 8

A Proposed Learner Activity Taxonomy and a Framework for Analysing Learner Engagement versus Performance Using Big Educational Data 一个建议的学习者活动分类和一个使用大教育数据分析学习者投入与表现的框架

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-13 DOI: 10.1109/CBMS.2017.160

S. Konstantinidis, Aaron Fecowycz, K. Coolin, H. Wharrad, G. Konstantinidis, P. Bamidis

{"title":"A Proposed Learner Activity Taxonomy and a Framework for Analysing Learner Engagement versus Performance Using Big Educational Data","authors":"S. Konstantinidis, Aaron Fecowycz, K. Coolin, H. Wharrad, G. Konstantinidis, P. Bamidis","doi":"10.1109/CBMS.2017.160","DOIUrl":"https://doi.org/10.1109/CBMS.2017.160","url":null,"abstract":"The inclusion of information and communication technologies in Healthcare and Medical Education is a fact nowadays. Furthermore numerous virtual learning environments have been established in order to host both educational material and learners online activities. Online modules in a VLE can be designed in very different ways being part of different types of courses, while different models can be used to design the course based on what the creator aims to achieve. Thus, the types and the importance of the different elements of the online course may vary a lot. At the same time the need of a global approach to gather big educational data in order to provide valid meaning to the data through learning analytics and educational data mining is urgent. In order this to be achievable we propose a Learner Activity Taxonomy in which the different elements of the learners activity data can be categorised and a Learner Engagement Framework in which the importance of the different elements is vital in order for an analysis of the big educational data to provide a meaningful result. The initial application to practice of the Taxonomy and the Framework are presented based on data from 3 modules at 2 Universities, while the impact of them along with its limitations are discussed.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125162477","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

Real-Time Instrument Scene Detection in Screening GI Endoscopic Procedures 实时仪器场景检测筛查胃肠道内镜手术

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-10 DOI: 10.1109/CBMS.2017.42

Chuanhai Zhang, Wallapak Tavanapong, J. Wong, P. C. Groen, Jung-Hwan Oh

引用次数: 3

Using Prevalence Patterns to Discover Un-mapped Flowsheet Data in an Electronic Health Record Data Warehouse 使用流行模式发现电子健康记录数据仓库中未映射的流程图数据

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-10 DOI: 10.1109/CBMS.2017.122

A. Bokov, Angela Bos, Laura S. Manuel, Alfredo Tirado-Ramos, Pamela Kittrell, C. Jackson, Gail P. Olin

{"title":"Using Prevalence Patterns to Discover Un-mapped Flowsheet Data in an Electronic Health Record Data Warehouse","authors":"A. Bokov, Angela Bos, Laura S. Manuel, Alfredo Tirado-Ramos, Pamela Kittrell, C. Jackson, Gail P. Olin","doi":"10.1109/CBMS.2017.122","DOIUrl":"https://doi.org/10.1109/CBMS.2017.122","url":null,"abstract":"We have developed a data summarization tool called Chi2notype which leverages the star schema of the Integrating Informatics from Bench to Bedside (i2b2) vendor-neutral data-warehouse platform to characterize a patient-cohort of interest. Chi2notype calculates a chi-squared statistic for every one of the hundreds of thousands of variables in an Electronic Medical Record (EMR) system and uses it to rank them from most over-represented in the cohort to most under-represented. This can be used for many purposes, including detection of adverse events, studies of socioeconomic disparities in health outcomes, and quality control. Here we demonstrate the use of Chi2notype to find un-mapped elements from nursing flowsheets used for monitoring the progress of ALS patients, thus making it possible to link them to their respective parent flowsheets in the i2b2 ontology. This, in turn, makes these flowsheets accessible to researchers performing eligibility queries or retrospective analysis on de-identified electronic health record (EHR) data.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114103924","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

The 360QS Toolkit for Sleep and Physical Activity Analysis Based on Wearables 基于可穿戴设备的360QS睡眠和身体活动分析工具包

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-10 DOI: 10.1109/CBMS.2017.72

Meghna Singh, L. Fernández-Luque, Jaideep Srivastava

引用次数: 1

Predicting Cognitive Recovery of Stroke Patients from the Structural MRI Connectome Using a Naïve Bayesian Tree Classifier 利用Naïve贝叶斯树分类器预测脑卒中患者结构MRI连接组的认知恢复

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-11-10 DOI: 10.1109/CBMS.2017.106

R. Dacosta-Aguayo, C. Stephan-Otto, T. Auer, Inmaculada Clemente, A. Dávalos, N. Bargalló, M. Mataró, M. Klados

{"title":"Predicting Cognitive Recovery of Stroke Patients from the Structural MRI Connectome Using a Naïve Bayesian Tree Classifier","authors":"R. Dacosta-Aguayo, C. Stephan-Otto, T. Auer, Inmaculada Clemente, A. Dávalos, N. Bargalló, M. Mataró, M. Klados","doi":"10.1109/CBMS.2017.106","DOIUrl":"https://doi.org/10.1109/CBMS.2017.106","url":null,"abstract":"Successful post-stroke prognosis and recovery strategies are heavily dependent on our understanding about how the damage to one specific region may impact to other remote regions, as well as the various functional networks involved in efficient cognitive function. In this study, 27 consecutive ischemic stroke patients were recruited. Stroke patients underwent two complete neuropsychological assessments between the first 72 hours after stroke arrival and three months later. They were further evaluated with a MRI protocol at 3 months. Patients were splitted into two groups according to their level of cognitive recovery. A data mining technique was then applied to the probabilistic tractography data in order to determine whether the structural connectivity features can efficiently classify good from poor recovery. We found that the connectivity probability between the left Superior Parietal Gyrus and the left Angular Gyrus can describe the cognitive classification (good versus poor recovery) after stroke. Both regions are involved in higher cognitive functioning and their dysfunction has been related to mild cognitive impairment and dementia. Our findings suggest that cognitive prognosis, in stroke patients, mainly depends on the connection of these two regions. An accurate model for the early prediction of stroke recovery as the one presented herein is fundamental to develop early personalized rehabilitation strategies.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134184824","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

The Design of a Mobile App for Promotion of Physical Activity and Self-Management in Prostate Cancer Survivors: Personas, Feature Ideation and Low-Fidelity Prototyping 促进前列腺癌幸存者身体活动和自我管理的移动应用程序设计:人物角色，功能构思和低保真原型

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-22 DOI: 10.1109/CBMS.2017.75

Francisco Monteiro-Guerra, O. Rivera, Vasiliki Mylonopoulou, G. Signorelli, Francisco Zambrana, L. Fernández-Luque

{"title":"The Design of a Mobile App for Promotion of Physical Activity and Self-Management in Prostate Cancer Survivors: Personas, Feature Ideation and Low-Fidelity Prototyping","authors":"Francisco Monteiro-Guerra, O. Rivera, Vasiliki Mylonopoulou, G. Signorelli, Francisco Zambrana, L. Fernández-Luque","doi":"10.1109/CBMS.2017.75","DOIUrl":"https://doi.org/10.1109/CBMS.2017.75","url":null,"abstract":"Most prostate cancer survivors are confronted with disease-related and treatment-related side effects that impact their quality of life. A tool that combines specific physical activity coaching with the promotion of a healthy lifestyle and self-management guidance might be a successful method to enhance a lifestyle change in these patients. As a prerequisite for useful health technology, it is important to consider a design process centred in the patients. The aim of this study was to investigate the context of the problem and the user needs to support the ideation of a low-fidelity prototype of a tool to promote a healthy lifestyle in survivors of early-stage prostate cancer survivors. A user-centred design approach was followed involving a multidisciplinary team. The prototype was developed in 3 phases. In phase 1, the context was studied with 2 systematic reviews of the state of practice and consulting with 3 specialists in Oncology, resulting in a global use case and main requirements. In phase 2, the needs and barriers of the users were studied based on literature research and validated with 3 specialists, resulting in the creation of 3 personas. In phase 3, 2 sessions were held to ideate and prioritize possible app features, based on brainstorming and selection techniques. Using the Ninja Mock and Proto.io software a low-fidelity prototype was developed, resulting in 25 interactive screens. Understanding the user needs and context seems to be essential to highlight key goals hence facilitating the bridge between ideation of the tool and the intended users tasks and experiences. The conclusion of this first stage of the design process brings valuable details (such as barriers of the users to technology and physical activity) for future iterations of design of the mobile app.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"109 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126108046","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