2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)最新文献_第9页

Care Coordination: A Systematic Review and a New Perspective 护理协调:系统回顾与新视角

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00007

P. Jain, Ankur Agarwal, Ravi S. Behara

引用次数: 1

Public Health Policy for Management of Hearing Impairments Based on Big Data Analytics: EVOTION at Genesis 基于大数据分析的听力障碍管理公共卫生政策:Genesis的进化

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00006

G. Spanoudakis, P. Katrakazas, D. Koutsouris, D. Kikidis, A. Bibas, N. H. Pontoppidan

{"title":"Public Health Policy for Management of Hearing Impairments Based on Big Data Analytics: EVOTION at Genesis","authors":"G. Spanoudakis, P. Katrakazas, D. Koutsouris, D. Kikidis, A. Bibas, N. H. Pontoppidan","doi":"10.1109/BIBE.2017.00006","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00006","url":null,"abstract":"The holistic management of hearing loss (HL) requires appropriate public health policies for HL prevention, early diagnosis, long-term treatment and rehabilitation; detection and prevention of cognitive decline; protection from noise; and socioeconomic inclusion of HL patients. However, currently the evidential basis for forming such policies is limited. Holistic HL management policies require the analysis of heterogeneous data, including Hearing Aid (HA) usage, noise episodes, audiological, physiological, cognitive, clinical and medication, personal, behavioural, life style, occupational and environmental data. To utilise these data in forming holistic HL management policies, EVOTION, a new European research and innovation project, aims to develop an integrated platform supporting: (a) the analysis of related datasets to enable the identification of causal and other effects amongst them using various forms of big data analytics, (b) policy decision making focusing on the selection of effective interventions related to the holistic management of HL, based on the outcomes of (a) and the formulation of related public health policies, and (c) the specification and monitoring of such policies in a sustainable manner. In this paper, we describe the EVOTION approach.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"519 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131966037","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: 17

Early Studies of a Transmission Mechanism for MR-Guided Interventions 核磁共振引导干预传播机制的早期研究

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-13

Haoran Zhao, Xin Liu, H. M. Zaid, D. Shah, M. Heffernan, Aaron T. Becker, N. Tsekos

{"title":"Early Studies of a Transmission Mechanism for MR-Guided Interventions","authors":"Haoran Zhao, Xin Liu, H. M. Zaid, D. Shah, M. Heffernan, Aaron T. Becker, N. Tsekos","doi":"10.1109/BIBE.2017.00-13","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00-13","url":null,"abstract":"Magnetic resonance imaging (MRI)-guided, manipulator-assisted interventions have the potential to improve patient outcomes. This work presents a force transmission mechanism, called solid-media transmission (SMT), for actuating manipulators inside MRI scanners. The SMT mechanism is based on conduits filled with spheres and spacers made of a nonmagnetic, nonconductive material that forms a backbone for bidirectional transmission. Early modeling and experimental studies assessed SMT and identified limitations and improvements. Simulations demonstrated the detrimental role of friction, which can be alleviated with a choice of low friction material and long spacers. However, the length of the spacer is limited by the desired bending of the conduit. A closed-loop control law was implemented to drive the SMT. The 3rd order system fit ratio is 92.3%. A 1-m long SMT was experimentally tested under this closed-loop controller with heuristically set parameters using a customized benchtop setup. For commanded displacements of 1 to 50 mm, the SMT-actuated 1 degree of freedom stage exhibited sub-millimeter accuracy, which ranged from 0.109 ± 0:057 mm to 0.045 ± 0.029 mm depending on the commanded displacement. However, such accuracy required long control times inversely proportional to displacement ranging from 7.56 ± 1.85s to 2.53 ± 0.11s. This was attributed to friction as well as backlash which is due to suboptimal packing of the media. In MR studies, a 4-m long SMT-actuated 1 DoF manipulator was powered by a servo motor located inside the scanner room but outside the 5 Gauss line of the magnet. With shielding and filtering, the SNR of MR images during the operation of the servo motor and SMT- actuation was found to be 89 ± 9% of the control case.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"575 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132559576","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

Novel Computational Approach for Identification of Highly Mutated Integrated HIV Genomes 一种新的计算方法用于鉴定高度突变的HIV整合基因组

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-47

K. Khanipov, L. Albayrak, G. Golovko, M. Pimenova, Ioannis T. Pavlidis, Y. Fofanov, K. Khanipov

引用次数: 0

Towards Centralized MS/MS Spectra Preprocessing: An Empirical Evaluation of Peptides Search Engines using Ground Truth Datasets 迈向集中的质谱/质谱预处理:使用地面真实数据集的肽搜索引擎的经验评估

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-56

Majdi Maabreh, Ajay K. Gupta, I. Alsmadi

{"title":"Towards Centralized MS/MS Spectra Preprocessing: An Empirical Evaluation of Peptides Search Engines using Ground Truth Datasets","authors":"Majdi Maabreh, Ajay K. Gupta, I. Alsmadi","doi":"10.1109/BIBE.2017.00-56","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00-56","url":null,"abstract":"several peptides search engines have been developed in the recent decades. Most of the time and for the same inputs, different search enginesâ€™ result in different peptides were identified, which can confuse the stakeholders in the field of proteomics. The massive amount of generated spectra by high throughput spectrometers adds another challenge which handicaps the current search engines. This motivates the researchers to evaluate the combination of several search engines. Several studies provided ensemble solutions over shared and distributed computing environments for reliable results. However, the massive amount of MS/MS spectra is a cumbersome traffic over the systemsâ€™ networks. This issue directly impacts the searching performance and also adds unnecessary extra costs (computing, storage, network traffic) if cloud cluster is being used. The main question of this paper is: Can we build a central MS/MS spectra preprocessing for semantically different protein search engines? We evaluate different statistical reduction techniques using four popular protein search engines. In order to fairly evaluate the results, we build ground truth unanimous-based datasets for two different species; yeast and human. Our techniques result in significant peak reduction, where only around 30% of the spectra peaks are enough to report reliable identifications from the used search engines in this study.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129423179","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

A novel low-complexity framework in ultra-wideband imaging for breast cancer detection 一种用于乳腺癌检测的新型低复杂度超宽带成像框架

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-09-08 DOI: 10.1109/BIBE.2017.8469114

Yasaman Ettefagh, M. H. Moghaddam, Saeed Vahidian

{"title":"A novel low-complexity framework in ultra-wideband imaging for breast cancer detection","authors":"Yasaman Ettefagh, M. H. Moghaddam, Saeed Vahidian","doi":"10.1109/BIBE.2017.8469114","DOIUrl":"https://doi.org/10.1109/BIBE.2017.8469114","url":null,"abstract":"In this research work, a novel framework is proposed as an efficient successor to traditional imaging methods for breast cancer detection in order to decrease the computational complexity. In this framework, the breast is divided into segments in an iterative process and in each iteration, the one having the most probability of containing tumor with lowest possible resolution is selected by using suitable decision metrics. After finding the smallest tumor-containing segment, the resolution is increased in the detected tumor-containing segment, leaving the other parts of the breast image with low resolution. Our framework is applied on the most common used beamforming techniques, such as delay and sum (DAS) and delay multiply and sum (DMAS) and according to simulation results, our framework can decrease the computational complexity significantly for both DAS and DMAS without imposing any degradation on accuracy of basic algorithms. The amount of complexity reduction can be determined manually or automatically based on two proposed methods that are described in this framework.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126088228","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

Whole Genome Phylogenetic Tree Reconstruction Using Colored de Bruijn Graphs 用彩色de Bruijn图重建全基因组系统发育树

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-09-01 DOI: 10.1109/BIBE.2017.00-44

Cole A. Lyman, M. Fujimoto, Anton Suvorov, P. Bodily, Q. Snell, K. Crandall, S. Bybee, M. Clement

引用次数: 1

Encoding Multi-Resolution Brain Networks Using Unsupervised Deep Learning 使用无监督深度学习编码多分辨率大脑网络

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-08-13 DOI: 10.1109/BIBE.2017.00-75

Arash Rahnama, Abdullah Alchihabi, V. Gupta, P. Antsaklis, F. Yarman-Vural

{"title":"Encoding Multi-Resolution Brain Networks Using Unsupervised Deep Learning","authors":"Arash Rahnama, Abdullah Alchihabi, V. Gupta, P. Antsaklis, F. Yarman-Vural","doi":"10.1109/BIBE.2017.00-75","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00-75","url":null,"abstract":"The main goal of this study is to extract a set of brain networks in multiple time-resolutions to analyze the connectivity patterns among the anatomic regions for a given cognitive task. We suggest a deep architecture which learns the natural groupings of the connectivity patterns of human brain in multiple time-resolutions. The suggested architecture is tested on task data set of Human Connectome Project (HCP) where we extract multi-resolution networks, each of which corresponds to a cognitive task. At the first level of this architecture, we decompose the fMRI signal into multiple sub-bands using wavelet decompositions. At the second level, for each sub-band, we estimate a brain network extracted from short time windows of the fMRI signal. At the third level, we feed the adjacency matrices of each mesh network at each time-resolution into an unsupervised deep learning algorithm, namely, a Stacked De- noising Auto-Encoder (SDAE). The outputs of the SDAE provide a compact connectivity representation for each time window at each sub-band of the fMRI signal. We concatenate the learned representations of all sub-bands at each window and cluster them by a hierarchical algorithm to find the natural groupings among the windows. We observe that each cluster represents a cognitive task with a performance of 93% Rand Index and 71% Adjusted Rand Index. We visualize the mean values and the precisions of the networks at each component of the cluster mixture. The mean brain networks at cluster centers show the variations among cognitive tasks and the precision of each cluster shows the within cluster variability of networks, across the subjects.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127770645","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

Validity of Biosignal Processing System based on Haar Transform in IoT Application 基于Haar变换的生物信号处理系统在物联网应用中的有效性

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-07-01 DOI: 10.1109/BIBE.2017.00-54

Yoonsu Shin, Jongseo Lee, Songkuk Kim

{"title":"Validity of Biosignal Processing System based on Haar Transform in IoT Application","authors":"Yoonsu Shin, Jongseo Lee, Songkuk Kim","doi":"10.1109/BIBE.2017.00-54","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00-54","url":null,"abstract":"In the Internet of Things (IoT) era, people are very interested in wearable devices such as smart watches. These devices measure individual physiological time series such as blood pressure, heart rate, and EEG. With this functionality, people can check the status of their own health. This healthcare service usually sends individual physiological time series to remote clusters for calculation. A remote healthcare service is particularly necessary for patients suffering from chronic and urgent diseases such as cardiovascular disease. It is also necessary to predict urgent signals for proper treatment. One method to predict urgent signals is by clustering physiological time series and comparing the new physiological time series with the previous time series in a cluster. It means searching the time series similar to risk features. In other words, the detection and comparison of features in time series are important. Therefore, in this study, we propose a biosignal processing system based on the Haar transform of time series in IoT applications. We discuss the validity of this system according to various perspectives. The Haar transform of a time series reflects the trend of the time series; thus, we can recognize the trend of the time series more easily. In addition, we can reduce the storage size of the time series. This is especially helpful because the volume of a time series is massive in the IoT era. Although the reduction of information in a time series can distort the similarity accuracy, it does not distort it significantly.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121071444","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

Exploration of Natural Alignment Scoring Rules and Clustering Thresholds for Bacterial Core/Pan Genome Analysis 细菌核心/泛基因组分析的自然比对评分规则和聚类阈值探索

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-07-01 DOI: 10.1109/BIBE.2017.00-46

L. Albayrak, K. Khanipov, M. Rojas, G. Golovko, M. Pimenova, M. Kosoy, Y. Fofanov

引用次数: 1