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Int. J. Funct. Informatics Pers. Medicine最新文献

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LFXtractor: Text chunking for long form detection from biomedical text LFXtractor:用于生物医学文本长格式检测的文本分块
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2010-11-30 DOI: 10.1504/IJFIPM.2010.037148
Min Song, Hongfang Liu
{"title":"LFXtractor: Text chunking for long form detection from biomedical text","authors":"Min Song, Hongfang Liu","doi":"10.1504/IJFIPM.2010.037148","DOIUrl":"https://doi.org/10.1504/IJFIPM.2010.037148","url":null,"abstract":"In this paper, we propose a novel method to detect the corresponding long forms (LFs) of short forms (SFs) from biomedical text. The proposed method is differentiated from others as follows: it incorporates lexical analysis techniques into supervised learning for extracting abbreviations; it utilises text-chunking techniques to identify LFs of abbreviations; it significantly improves recall. The experimental results show that our approach outperforms the leading abbreviation algorithms, ExtractAbbrev, ALICE and Acrophile and a collocation-based approach at least by 4.8, 6.0, 9.0 and 6.0%, respectively, in both precision and recall on the Gold Standard Development corpus.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117296477","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
RE-PLAN: a computational framework for REsponse PLan ANalysis RE-PLAN:响应计划分析的计算框架
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2010-11-30 DOI: 10.1504/IJFIPM.2010.037149
Tamara Schneider, Armin R. Mikler
{"title":"RE-PLAN: a computational framework for REsponse PLan ANalysis","authors":"Tamara Schneider, Armin R. Mikler","doi":"10.1504/IJFIPM.2010.037149","DOIUrl":"https://doi.org/10.1504/IJFIPM.2010.037149","url":null,"abstract":"Lurking pandemics and ever-present bio-terror threats necessitate the design of contingency plans that address these bio-emergencies. Continuous changes in regional demographics and transportation infrastructure imply that response plans are not static, but undergo frequent revisions. These plans outline specific response scenarios attempting to meet federal mandated performance criteria. However, there are only few computational tools available that can aid in the analysis of response plan performance. REsponse PLan ANalyser (RE-PLAN), a computational framework with GIS capabilities, facilitates the analysis of response plans and their corresponding placement of resources. This paper introduces the RE-PLAN architecture and its underlying methodologies. The principles of plan analysis are demonstrated by applying RE-PLAN to a synthetically generated geographic region and the results of each analysis step are shown.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132901552","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
An integrated service for Personalised Healthcare and Wellness (PHW) 个人化医疗保健及健康综合服务
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2010-11-30 DOI: 10.1504/IJFIPM.2010.037151
Su-shing Chen
{"title":"An integrated service for Personalised Healthcare and Wellness (PHW)","authors":"Su-shing Chen","doi":"10.1504/IJFIPM.2010.037151","DOIUrl":"https://doi.org/10.1504/IJFIPM.2010.037151","url":null,"abstract":"At the Systems Biology Lab of the University of Florida, we are developing an integrated system, PHW service, for accessing and storing and monitoring information in personalised medicine. We intend to take a practical approach to build such a system in the framework of clinical and translational sciences of the NIH Roadmap.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132587691","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
Hybrid Support Vector Machine for imbalanced data in multiclass arrhythmia classification 多类心律失常不平衡数据的混合支持向量机分类
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2010-05-17 DOI: 10.1504/IJFIPM.2010.033244
Aniruddha J. Joshi, S. Chandran, V. Jayaraman, B. Kulkarni
{"title":"Hybrid Support Vector Machine for imbalanced data in multiclass arrhythmia classification","authors":"Aniruddha J. Joshi, S. Chandran, V. Jayaraman, B. Kulkarni","doi":"10.1504/IJFIPM.2010.033244","DOIUrl":"https://doi.org/10.1504/IJFIPM.2010.033244","url":null,"abstract":"Automatically classifying ECG recordings for arrhythmia is difficult since even normal ECG signals exhibit irregularities, and learning algorithms suffer from class imbalance. We propose a hybrid SVM to combat class imbalance rampant in biomedical signals. Consequently, we significantly reduce the number patients falsely classified as normal. The Hybrid SVM is suitable for a variety of multiclass problems; here, we used the MIT-BIH Arrhythmia database, and the position and magnitude of local singularities as features. We enhance relevant singularity-driven Holder features proposed earlier; while the use of these features results in higher accuracy, using the Hybrid SVM shows even more gains.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126814745","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
MOACO Biclustering of gene expression data 基因表达数据的MOACO双聚类
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2010-05-17 DOI: 10.1504/IJFIPM.2010.033246
Junwan Liu, Zhoujun Li, Xiaohua Hu, Yiming Chen
{"title":"MOACO Biclustering of gene expression data","authors":"Junwan Liu, Zhoujun Li, Xiaohua Hu, Yiming Chen","doi":"10.1504/IJFIPM.2010.033246","DOIUrl":"https://doi.org/10.1504/IJFIPM.2010.033246","url":null,"abstract":"Many bioinformatics data sets come from DNA microarray experiments. Biclustering of gene expression data can identify genes with similar behaviour with respect to different conditions. Ant Colony Optimisation (ACO) algorithms have been shown to be effective problem solving strategies for a wide range of problem domains. Multiple Objective Ant Colony Optimisation (MOACO) mainly focuses on solving the multiple objective combinatorial optimisation problems. This paper incorporates crowding update technology into MOACOB and proposes crowding MOACO biclustering algorithm to mine biclusters from gene expression data. Experimental results are shown for biclustering algorithm on two real gene expression data.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129762894","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
Analysis of microarray data to infer transcription regulation in the yeast cell cycle 分析微阵列数据推断酵母细胞周期中的转录调控
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2010-05-17 DOI: 10.1504/IJFIPM.2010.033247
Akther Shermin, M. Orgun
{"title":"Analysis of microarray data to infer transcription regulation in the yeast cell cycle","authors":"Akther Shermin, M. Orgun","doi":"10.1504/IJFIPM.2010.033247","DOIUrl":"https://doi.org/10.1504/IJFIPM.2010.033247","url":null,"abstract":"The experimental microarray data has the potential application in determining the underlying mechanisms of transcription regulation in a living cell. The inference of this regulation circuitry with computational methods suffers from two major challenges: the low accuracy of inferring true positive connections and the excessive computation time. In this paper, we show that models based on Dynamic Bayesian Networks which exploit the biological features of gene expression are more computationally efficient and topologically accurate compared to the other existing models. Using two experimental microarray datasets of the yeast cell cycle, we also evaluate how successfully the available models can address the current challenges with the increasing size of the datasets.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"11 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128507368","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
Non-Rigid Registration for brain MRI: faster and cheaper 脑MRI非刚性配准:更快更便宜
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2010-05-17 DOI: 10.1504/IJFIPM.2010.033245
Yixun Liu, Andrey Fedorov, R. Kikinis, N. Chrisochoides
{"title":"Non-Rigid Registration for brain MRI: faster and cheaper","authors":"Yixun Liu, Andrey Fedorov, R. Kikinis, N. Chrisochoides","doi":"10.1504/IJFIPM.2010.033245","DOIUrl":"https://doi.org/10.1504/IJFIPM.2010.033245","url":null,"abstract":"We study the problem of Non-Rigid Registration (NRR) for intra-operative recovery of brain shift during image-guided neurosurgery. Time-critical nature of the tumour resection procedure presents a major obstacle to the routine clinical use of many available NRR approaches. In this paper, we utilise the resources of a single multicore workstation with an advanced graphics card to parallelise and evaluate an end-to-end implementation of a clinically validated NRR method. The results on clinical brain MRI data show the parallel NRR can reach real-time clinical requirement.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123610690","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: 5
Automatic extraction of proximal femur contours from calibrated X-ray images: a Bayesian inference approach 从校准的x射线图像中自动提取股骨近端轮廓:贝叶斯推理方法
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2009-08-03 DOI: 10.1504/IJFIPM.2009.027594
Xiao Dong, Guoyan Zheng
{"title":"Automatic extraction of proximal femur contours from calibrated X-ray images: a Bayesian inference approach","authors":"Xiao Dong, Guoyan Zheng","doi":"10.1504/IJFIPM.2009.027594","DOIUrl":"https://doi.org/10.1504/IJFIPM.2009.027594","url":null,"abstract":"Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. This paper proposed a 3D-statistical-model-based framework for the proximal femur bone contour extraction from calibrated X-ray images. The initialisation to align the statistical model is solved by a particle filter on a dynamic Bayesian network to fit a multiple component geometrical model to the X-ray images. The contour extraction is accomplished by a non-rigid 2D?3D registration between the X-ray images and the statistical model, in which bone contours are extracted by a graphical-model-based Bayesian inference. Experiments on clinical data set verified its robustness against occlusion.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124473865","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
Br-SDM: a fast and accurate method for bone-related soft tissue prediction in orthognathic surgery planning based on the integration of SDM and FEM Br-SDM:一种基于SDM和FEM相结合的正颌手术计划中骨相关软组织快速准确预测方法
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2009-08-03 DOI: 10.1504/IJFIPM.2009.027593
Q. He, Jun Feng, H. Ip, J. Xia, Xianbin Cao
{"title":"Br-SDM: a fast and accurate method for bone-related soft tissue prediction in orthognathic surgery planning based on the integration of SDM and FEM","authors":"Q. He, Jun Feng, H. Ip, J. Xia, Xianbin Cao","doi":"10.1504/IJFIPM.2009.027593","DOIUrl":"https://doi.org/10.1504/IJFIPM.2009.027593","url":null,"abstract":"We propose a novel Statistical Deformable Model (SDM) for bone-related soft tissue prediction, which we called Br-SDM. In Br-SDM, we have integrated Finite Element Method (FEM) and SDM to achieve both accurate and efficient prediction for orthognathic surgery planning. By combining FEM-based sample generation and SDM-Based soft tissue prediction, we are able to capture the prior knowledge of bone-related soft tissue deformation. Then the post-operative appearance can be predicted in a more efficient way from a Br-SDM based optimisation. Our experiments have shown that Br-SDM is able to give comparable soft tissue prediction accuracy with respect to conventional FEM-based prediction while reducing the computation cost from O(n²) to O(n) at the same time.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"55 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132242583","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
Correction of susceptibility-induced distortion in Diffusion Tensor Imaging with a moment-based phase unwrapping method 基于矩的相位展开法校正扩散张量成像中磁化率畸变
Int. J. Funct. Informatics Pers. Medicine Pub Date : 2009-08-03 DOI: 10.1504/IJFIPM.2009.027588
Qun Zhao, J. Langley, C. Faraco, L. Miller
{"title":"Correction of susceptibility-induced distortion in Diffusion Tensor Imaging with a moment-based phase unwrapping method","authors":"Qun Zhao, J. Langley, C. Faraco, L. Miller","doi":"10.1504/IJFIPM.2009.027588","DOIUrl":"https://doi.org/10.1504/IJFIPM.2009.027588","url":null,"abstract":"Diffusion Tensor Imaging (DTI) is a powerful technique for non-invasive characterisation of normal and pathological tissues, however, it is vulnerable to geometric distortions caused by magnetic field inhomogeneity. In this work, we present a phase unwrapping method that is based on the method of moments. The algorithm is used to generate magnetic field maps and correct susceptibility-induced distortions. MR datasets were acquired using a 3T MRI scanner to investigate consistency of distortion correction by the proposed method. The results demonstrate the relative consistency of the resultant distortion correction, which is critical for longitudinal studies of human diseases using DTI.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124904910","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
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