2014 IEEE 27th International Symposium on Computer-Based Medical Systems最新文献

Package Insert Leaflet Analysis and Improvement to Reduce Patient Risk Factors: A Pharmacovigilance Approach in Computer Science 药品说明书分析和改进以减少患者风险因素:计算机科学中的药物警戒方法

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.101

Fabian Merges, S. Nasiri, M. Fathi

引用次数: 0

Towards the Stress Analytics Framework: Managing, Mining, and Visualizing Multi-modal Data for Stress Awareness 迈向应力分析框架:管理，挖掘和可视化多模态数据的压力意识

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.129

Hindra Kurniawan, Mykola Pechenizkiy

引用次数: 2

Identifying and Evaluating Usability Heuristics Applicable to Clinical Laboratory Systems 识别和评估适用于临床实验室系统的可用性启发式

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.123

J. M. Alves, C. V. Wangenheim, Alexandre Savaris, A. V. Wangenheim

引用次数: 5

Innovative Computerized Non-invasive Intracranial Pressure Measurement Technology and Its Clinical Validation 创新的计算机无创颅内压测量技术及其临床验证

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.40

S. Krakauskaite, V. Petkus, R. Zakelis, L. Bartusis, R. Chomskis, A. Ragauskas

引用次数: 1

An Adaptive Testing Model for Assessment of Numeracy in Patients 一种评估患者算术能力的适应性测试模型

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.97

M. Omidbakhsh, T. Radhakrishnan

引用次数: 3

miXGENE Tool for Learning from Heterogeneous Gene Expression Data Using Prior Knowledge miXGENE工具用于使用先验知识从异质基因表达数据中学习

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.8

Matej Holec, Valentin Gologuzov, J. Kléma

{"title":"miXGENE Tool for Learning from Heterogeneous Gene Expression Data Using Prior Knowledge","authors":"Matej Holec, Valentin Gologuzov, J. Kléma","doi":"10.1109/CBMS.2014.8","DOIUrl":"https://doi.org/10.1109/CBMS.2014.8","url":null,"abstract":"High-throughput genomic technologies have proved to be useful in the search for both genetic disease markers and more complex predictive and descriptive models. By the same token, it became obvious that accurate and interpretable models need to concern more than raw measurements taken at a single phase of gene expression. In order to reach a deeper understanding of the molecular nature of complexly orchestrated biological processes, all the available measurements and existing genomic knowledge need to be fused. In this paper, we introduce a tool for machine learning from heterogeneous gene expression data using prior knowledge. The tool is called miXGENE, it is elaborated upon in close connection with the biological departments that dispose of the above-mentioned data and have a strong interest in their integration within particular problem-oriented projects. The main idea is not merely to capture the transcriptional phase of gene expression quantified by the amount of messenger RNA (mRNA). The increasing availability of microRNA (miRNA) data asks for its concurrent analysis with the transcriptional data. Moreover, epigenetic data such as methylation measurements can help to explain unexpected transcriptional irregularities. miXGENE is an environment for building workflows that enable rapid prototyping of integrative molecular models.","PeriodicalId":398710,"journal":{"name":"2014 IEEE 27th International Symposium on Computer-Based Medical Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123774322","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

Comparative Analysis of Golay Code Based Excitation and Coherent Averaging for Non-invasive Glucose Monitoring System 基于Golay码的激励与相干平均在无创血糖监测系统中的比较分析

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.102

Satyabrata Sarangi, Praful P. Pai, P. K. Sanki, S. Banerjee

引用次数: 4

Expanding the HCI Agenda in Healthcare 扩大医疗保健领域的HCI议程

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.15

B. Kane, S. Luz

引用次数: 1

NerveGPS: A Novel Decision Support System for Ultrasound Nerve Block Guidance NerveGPS:一种新的超声神经阻滞引导决策支持系统

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.34

C. Philippona, J. Morse, M. Wehbe, M. Giacalone, S. Cyr, R. Kazan, T. Hemmerling

{"title":"NerveGPS: A Novel Decision Support System for Ultrasound Nerve Block Guidance","authors":"C. Philippona, J. Morse, M. Wehbe, M. Giacalone, S. Cyr, R. Kazan, T. Hemmerling","doi":"10.1109/CBMS.2014.34","DOIUrl":"https://doi.org/10.1109/CBMS.2014.34","url":null,"abstract":"Peripheral regional nerve blockade (nerve block) is used in anesthesia to administer anesthesia to certain regions of the body. During nerve block the anesthetic is injected directly into or around the area surrounding the nerve. One of the most critical components of ultrasound-guided nerve blocks is the detection of the nerve within the ultrasound image. This study presents a software-based solution for the detection of nerves within the ultrasound feed. The software that was developed used image processing tools to detect the location of the sciatic nerve at the popliteal fossa within an ultrasound feed. For the study, 100 images were obtained from authors. Then, 2 anesthesiologists with experience in ultrasound-guided nerve blocks were asked to identify the contour of the nerve in the obtained images. The study used two criteria for evaluating the software: 1) the location of the software determined nerve center fell within the manually defined contour and 2) the percentage of overlap between the software and manually detected areas. A test was successful if the percentage of overlap between automatic and manual detection was a minimum of 95% for a circle of 0.4cm diameter centered at the software detected nerve center. For the 100 image sample, the nerve was detected within the manually detected area in 99% of the cases, with an overlap of 98% for a 0.4cm diameter circle. Time to detect the nerve ranged from 0.95s to 1.6s. These preliminary results show that the nerve detection software provides a reliable target for needle insertion. Future work will extend the software to different nerves of interest.","PeriodicalId":398710,"journal":{"name":"2014 IEEE 27th International Symposium on Computer-Based Medical Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126766555","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: 3

Robust Visual Tracking for Retinal Mapping in Computer-Assisted Slit-Lamp Imaging 计算机辅助裂隙灯成像中视网膜映射的鲁棒视觉跟踪

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.53

M. Souza, Rogério Richa, A. Puel, Jonas Caetano, E. Comunello, A. V. Wangenheim

引用次数: 5