2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)最新文献_第10页

A Deconstructed Replication of a Time of Test Study Using the AGIS Metric 使用AGIS度量对测试时间研究的解构复制

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.60

S. Counsell, S. Swift, A. Tucker

引用次数: 1

Towards Patterns for Defining and Changing Data Collection Instruments in Mobile Healthcare Scenarios 在移动医疗场景中定义和更改数据收集工具的模式

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.61

Johannes Schobel, R. Pryss, Marc Schickler, M. Reichert

引用次数: 3

Studying the Potential of Multi-target Classification to Characterize Combinations of Classes with Skewed Distribution 研究多目标分类对偏斜分布类组合特征的潜力

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.136

Arne Schneck, S. Kalle, R. Pryss, W. Schlee, T. Probst, B. Langguth, M. Landgrebe, M. Reichert, M. Spiliopoulou

引用次数: 4

A Fall Prevention System for the Elderly: Preliminary Results 老年人跌倒预防系统:初步结果

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.130

Giuseppe Palestra, Mohamed Rebiai, E. Courtial, K. Giokas, D. Koutsouris

引用次数: 4

Random Walker with Fuzzy Initialization Applied to Segment Masses in Mammography Images 模糊初始化随机漫步器在乳房x线影像块分割中的应用

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.40

F. Cordeiro, Kallebe Felipe Pereira Bezerra, W. Santos

引用次数: 12

Disease-Based Clustering of Hospital Admission: Disease Network of Hospital Networks Approach 基于疾病的住院聚类:医院网络的疾病网络方法

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.87

Nouf Albarakati, Z. Obradovic

{"title":"Disease-Based Clustering of Hospital Admission: Disease Network of Hospital Networks Approach","authors":"Nouf Albarakati, Z. Obradovic","doi":"10.1109/CBMS.2017.87","DOIUrl":"https://doi.org/10.1109/CBMS.2017.87","url":null,"abstract":"To improve the quality of healthcare planning, healthcare systems face challenges in identifying clusters of similar hospitals while considering varying factors. Clustering hospitals based on their admission behavior would be helpful whereas diagnosis of patients is vital in understanding variation in admission. Therefore, grouping hospitals that show similar behavior on their admission distribution while considering similarity among disease symptoms in admission is the objective of our study. This is achieved by a Disease Network of Hospital Networks model which is used to represent hospital admission distribution of multiple diseases as different hospital networks that correspond to disease nodes in a top-layer disease network. This disease network that was extracted from the Human Symptoms Disease Network models the similarity among different disease-specific hospital networks. We assume that disease-specific hospital networks have different underlying clustering structure while share the same underlying clustering structure if corresponding diseases share similar symptoms. Experiments were conducted on more than 14 million electronic health records of monthly admission of 160 diseases over 4 years at 301 hospitals in California. Results of clustering 160 disease-specific hospitals networks that share similar symptoms among corresponding diseases show consistent behavior among these networks when similarity among diseases is considered in clustering process. Patterns of consistent behavior were lacking in results when similarity among diseases is not considered.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"23 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132477394","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: 4

Anomaly Detection Through Temporal Abstractions on Intensive Care Data: Position Paper 基于时间抽象的重症监护数据异常检测:立场文件

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.146

G. J. Gelatti, A. Carvalho, P. Rodrigues

{"title":"Anomaly Detection Through Temporal Abstractions on Intensive Care Data: Position Paper","authors":"G. J. Gelatti, A. Carvalho, P. Rodrigues","doi":"10.1109/CBMS.2017.146","DOIUrl":"https://doi.org/10.1109/CBMS.2017.146","url":null,"abstract":"A large amount of information is continuously generated in intensive health care. An analysis of these data streams can supply valuable insights to improve the monitoring of the patients. The volume, frequency and complexity of data, which come unlabeled, make their analysis a challenging task. Machine learning (ML) techniques have been successfully employed for mining data streams to extract useful knowledge for health care monitoring. It includes the detection of changes in the behavior of sensors, failures on machines or systems, and data anomalies. Anomaly (or outlier) detection is a ML task that aims to find exceptions or abnormalities in a dataset. These exceptions, in a medical context, can represent a new disease pattern, an event to be further investigated, behavior changes or potential health complications. Despite of its analysis in data streams is a challenging task, temporal abstractions techniques should help due to they deal with the management and abstraction of time based data, offering high level of visualization of each data object in its context. The aim of this paper is to review recent research in anomaly detection and temporal abstractions and discuss the application of their combination to intensive care data streams.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131453301","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

Mobile Crowdsensing for the Juxtaposition of Realtime Assessments and Retrospective Reporting for Neuropsychiatric Symptoms 移动人群感知对神经精神症状的实时评估和回顾性报告并立

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.100

R. Pryss, T. Probst, W. Schlee, Johannes Schobel, B. Langguth, P. Neff, M. Spiliopoulou, M. Reichert

{"title":"Mobile Crowdsensing for the Juxtaposition of Realtime Assessments and Retrospective Reporting for Neuropsychiatric Symptoms","authors":"R. Pryss, T. Probst, W. Schlee, Johannes Schobel, B. Langguth, P. Neff, M. Spiliopoulou, M. Reichert","doi":"10.1109/CBMS.2017.100","DOIUrl":"https://doi.org/10.1109/CBMS.2017.100","url":null,"abstract":"Many symptoms of neuropsychiatric disorders such as tinnitus are subjective and vary over time. Usually, in interviews or self-report questionnaires, patients are asked to report symptoms as well as their severity and duration retrospectively. However, only little is known to what degree such retrospective reports reflect the symptoms experienced in daily life some time ago. Mobile technologies can help to bridge this gap: mobile self-help services allow patients to record their symptoms prospectively when (or shortly after) they occur in daily life. In this study, we present results that we obtained with the mobile crowdsensing platform TrackYourTinnitus to show that there is a discrepancy between the prospective assessment of symptom variability and the retrospective report thereof. To be more precise, we evaluated the real-time entries provided to the platform by individuals experiencing tinnitus. The results indicate that mobile technologies like the TrackYourTinnitus crowdsensing platform may go beyond the role of an assistive service for patients by contributing to more accurate diagnosis and, hence, to a more elaborated treatment.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130874210","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: 19

Self-Adaptive Multi-objective Evolutionary Algorithm for Molecular Design 分子设计的自适应多目标进化算法

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.129

Christos C. Kannas, C. Pattichis

{"title":"Self-Adaptive Multi-objective Evolutionary Algorithm for Molecular Design","authors":"Christos C. Kannas, C. Pattichis","doi":"10.1109/CBMS.2017.129","DOIUrl":"https://doi.org/10.1109/CBMS.2017.129","url":null,"abstract":"Self-adaptation is an efficient way to control the strategy parameters of an Evolutionary Algorithm automatically during optimization. It is based on implicit evolutionary search in the space of strategy parameters, and has been proven to work well as on-line parameter control method for a variety of strategy parameters, from local to global ones. Our proposed Self-Adaptive Multi-Objective Evolutionary Algorithm is a two level algorithm. The proposed solution is applied on the problem of de novo molecular design. The outer level is the algorithm that is responsible for the self adaptive techniques and is based on Multi-Objective Genetic Algorithm. The inner level is based on the elite Multi-Objective Evolutionary Graph Algorithm. Both the outer and inner algorithms are variations of our previously proposed Multi-Objective Evolutionary Graph Algorithm framework. The outer Multi-Objective Genetic Algorithm operates on a chromosome of elements, while the inner elite Multi-Objective Evolutionary Graph Algorithm operates on molecular graph chromosomes. In general, the proposed solution: (i) searches a larger space, (ii) generates far more solutions per iteration, (iii) evaluates different sets of parameter options for the given problem, and (iv) proposes the fittest parameter sets that should be used for the given problem.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"368 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126705834","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

An Intermixed Color Paradigm for P300 Spellers: A Comparison with Gray-Scale Spellers P300拼写器的混合色范式:与灰度拼写器的比较

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-01 DOI: 10.1109/CBMS.2017.123

Mina R. Meshriky, S. Eldawlatly, G. Aly

{"title":"An Intermixed Color Paradigm for P300 Spellers: A Comparison with Gray-Scale Spellers","authors":"Mina R. Meshriky, S. Eldawlatly, G. Aly","doi":"10.1109/CBMS.2017.123","DOIUrl":"https://doi.org/10.1109/CBMS.2017.123","url":null,"abstract":"P300 speller systems represent one of the most basic applications of Brain-Computer Interfaces (BCIs). A traditional P300 speller consists of a 6 by 6 grid of characters in which each column or row in this grid intensifies at random. During such intensification process, the electroencephalography (EEG) data of the subject is recorded and analyzed to determine the character to be spelled. In this paper, we demonstrate how to improve on the traditional P300 speller by investigating the effects of incorporating different color luminance in the columns and rows of the spellers grid-of-characters (i.e. red, green and blue) as opposed to the conventional one-color (i.e. gray-scale) luminance. In our analysis, we used the Emotiv Neuroheadset to record scalp EEG obtained from the frontal, parietal and occipital brain regions. We examine four different feature extraction techniques in addition to two classifiers, namely, Linear Discriminant Analysis (LDA) and Linear Support vector machines (LSVM). Offline and online tests conducted on four subjects demonstrate a significant performance increase (up to 16%) for the intermixed color luminance case compared to the gray luminance one. These results indicate the efficacy of incorporating colors into P300 spellers interface.","PeriodicalId":141105,"journal":{"name":"2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123194247","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: 7