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Information Technology in Biomedicine, IEEE Transactions on

Issue 4 • Date July 2007

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Displaying Results 1 - 20 of 20
  • Table of contents

    Page(s): C1 - C4
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    Freely Available from IEEE
  • IEEE Transactions on Information Technology in Biomedicine publication information

    Page(s): C2
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    Freely Available from IEEE
  • Guest Editorial Introduction to the Special Issue on Biomedical Informatics: Research and Applications

    Page(s): 361 - 363
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    Freely Available from IEEE
  • A Field Theoretical Approach to Medical Natural Language Processing

    Page(s): 364 - 375
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (630 KB) |  | HTML iconHTML  

    A parser for medical free text reports has been developed that is based on a chemistry/physics inspired ldquofield theoryrdquo for word-word sentence-level dependencies. The transition from the linguistic world to the world of interacting particles with potential energies is guided by a psycholinguistics thought experiment related to the amount of ldquoworkrdquo required to bring a reference word into an anchored configuration of words. Calibration experiments involving four and five grams were conducted. Data from these experiments were used as a knowledge source for estimating field conditions for words in sentences sampled from a corpus of medical reports. The result of the parser is a dependency tree that represents the global minimum energy state of the system of words for a given sentence. The system was trained and tested on a corpus of radiology reports. Preliminary performance, as quantified by link recall and precision statistics, is 84.9% and 89.9%, respectively. View full abstract»

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  • Management and Analysis of Genomic Functional and Phenotypic Controlled Annotations to Support Biomedical Investigation and Practice

    Page(s): 376 - 385
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (583 KB) |  | HTML iconHTML  

    The growing available genomic information provides new opportunities for novel research approaches and original biomedical applications that can provide effective data management and analysis support. In fact, integration and comprehensive evaluation of available controlled data can highlight information patterns leading to unveil new biomedical knowledge. Here, we describe Genome Function INtegrated Discover (GFINDer ), a Web-accessible three-tier multidatabase system we developed to automatically enrich lists of user-classified genes with several functional and phenotypic controlled annotations, and to statistically evaluate them in order to identify annotation categories significantly over- or underrepresented in each considered gene class. Genomic controlled annotations from Gene Ontology (GO), KEGG, Pfam, InterPro, and online mendelian Inheritance in Man (OMIM) were integrated in GFINDer and several categorical tests were implemented for their analysis. A controlled vocabulary of inherited disorder phenotypes was obtained by normalizing and hierarchically structuring disease accompanying signs and symptoms from OMIM clinical synopsis sections. GFINDer modular architecture is well suited for further system expansion and for sustaining increasing workload. Testing results showed that GFINDer analyses can highlight gene functional and phenotypic characteristics and differences, demonstrating its value in supporting genomic biomedical approaches aiming at understanding the complex biomolecular mechanisms underlying patho-physiological phenotypes, and in helping the transfer of genomic results to medical practice. View full abstract»

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  • Modeling Drug Mechanism Knowledge Using Evidence and Truth Maintenance

    Page(s): 386 - 397
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (418 KB) |  | HTML iconHTML  

    To protect the safety of patients, it is vital that researchers find methods for representing drug mechanism knowledge that support making clinically relevant drug-drug interaction (DDI) predictions. Our research aims to identify the challenges of representing and reasoning with drug mechanism knowledge and to evaluate potential informatics solutions to these challenges through the process of developing a knowledge-based system capable of predicting clinically relevant DDIs that occur via metabolic mechanisms. In previous work, we designed a simple, rule-based, model of metabolic inhibition and induction and applied it to a database containing assertions about 267 drugs. This pilot system taught us that drug mechanism knowledge is often dynamic, missing, or uncertain. In this paper, we propose methods to address these properties of mechanism knowledge and describe a new prototype system, the Drug Interaction Knowledge-base (DIKB), that implements our proposed methods so that we can explore their strengths and limitations. A novel feature of the DIKB is its use of a truth maintenance system to link changes in the evidence support for assertions about drug properties to the set of interactions and non-interactions the system predicts. View full abstract»

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  • Optimal Search-Based Gene Subset Selection for Gene Array Cancer Classification

    Page(s): 398 - 405
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (333 KB) |  | HTML iconHTML  

    High dimensionality has been a major problem for gene array-based cancer classification. It is critical to identify marker genes for cancer diagnoses. We developed a framework of gene selection methods based on previous studies. This paper focuses on optimal search-based subset selection methods because they evaluate the group performance of genes and help to pinpoint global optimal set of marker genes. Notably, this paper is the first to introduce tabu search (TS) to gene selection from high-dimensional gene array data. Our comparative study of gene selection methods demonstrated the effectiveness of optimal search-based gene subset selection to identify cancer marker genes. TS was shown to be a promising tool for gene subset selection. View full abstract»

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  • On the Classification of Prostate Carcinoma With Methods from Spatial Statistics

    Page(s): 406 - 414
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (299 KB) |  | HTML iconHTML  

    Gleason grading is a common method used by pathologists to determine the aggressivity of prostate cancer on the basis of histological slide preparations. The advantage of this grading system is a good correlation with the biological behavior of the tumor, while its drawback is the subjectivity underlying the judgements of pathologists. Therefore, an automation of Gleason grading would be desirable. In this paper, we examined 780 digitized grayscale images of 78 different cases, which were split into a training and a test set. We developed two methods based on combinations of morphological characteristics like area fraction, line length, and Euler number to classify into the categories "Gleason score <7" and "Gleason score ges7." In particular, the distinction between these two classes has great impact on the prognosis of patients. The agreement of each method with visual diagnosis was 87.18% and 92.31% within the training set and 66.67% and 64.10% within the test set, respectively. View full abstract»

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  • Psychiatric Consultation Record Retrieval Using Scenario-Based Representation and Multilevel Mixture Model

    Page(s): 415 - 427
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (436 KB)  

    Psychiatric consultation record retrieval attempts to help people to efficiently and effectively locate the consultation records relevant to their depressive problems. Consultation records can also make people aware that they are not alone, because many individuals have suffered from the same or similar problems. Additionally, people can understand how to alleviate their depressive symptoms according to recommendations from health professionals. To achieve this goal, this paper proposes the use of a scenario-based representation, i.e., a symptom-based structural representation, to capture the depressive symptoms and their semantic relations, such as cause-effect and temporal relations, for understanding users' queries clearly. The symptoms and relations are identified from semantic mining and analysis of consultation records. The multilevel mixture model is adopted to estimate the relevance of queries and consultation records based on the structural information. Experimental results show that the proposed approach achieves higher precision than does a term-based flat representation. An experiment is also conducted to examine the effect of error propagation resulting from incorrect identification of symptoms and relations. Experimental results demonstrate that combining different approaches can improve the retrieval robustness. View full abstract»

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  • BAAQ: An Infrastructure for Application Integration and Knowledge Discovery in Bioinformatics

    Page(s): 428 - 434
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (582 KB) |  | HTML iconHTML  

    The emerging grid computing technologies enable bioinformatics scientists to conduct their researches in a virtual laboratory, in which they share public databases, computational tools as well as their analysis workflows. However, the development of grid applications is still a nightmare for general bioinformatics scientists, due to the lack of grid programming environments, standards and high-level services. Here, we present a system, which we named bioinformatics: ask any questions (BAAQ), to automate this development procedure as much as possible. BAAQ allows scientists to store and manage remote biological data and programs, to build analysis workflows that integrate these resources seamlessly, and to discover knowledge from available resources. This paper addresses two issues in building grid applications in bioinformatics: how to smoothly compose an analysis workflow using heterogeneous resources and how to efficiently discover and re-use available resources in the grid community. Correspondingly an intelligent grid programming environment and an active solution recommendation service are proposed. Finally, we present a case study applying BAAQ to a bioinformatics problem. View full abstract»

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  • Exploring Microbial Genome Sequences to Identify Protein Families on the Grid

    Page(s): 435 - 442
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    The analysis of microbial genome sequences can identify protein families that provide potential drug targets for new antibiotics. With the rapid accumulation of newly sequenced genomes, this analysis has become a computationally intensive and data-intensive problem. This paper describes the development of a Web-service-enabled, component-based, architecture to support the large-scale comparative analysis of complete microbial genome sequences and the subsequent identification of orthologues and protein families (Microbase). The system is coordinated through the use of Web-service-based notifications and integrates distributed computing resources together with genomic databases to realize all-against-all comparisons for a large volume of genome sequences and to present the data in a computationally amenable format through a Web service interface. We demonstrate the use of the system in searching for orthologues and candidate protein families, which ultimately could lead to the identification of potential therapeutic targets. View full abstract»

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  • Segmentation and Classification of Dot and Non-Dot-Like Fluorescence in situ Hybridization Signals for Automated Detection of Cytogenetic Abnormalities

    Page(s): 443 - 449
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (236 KB) |  | HTML iconHTML  

    Signal segmentation and classification of fluorescence in situ hybridization (FISH) images are essential for the detection of cytogenetic abnormalities. Since current methods are limited to dot-like signal analysis, we propose a methodology for segmentation and classification of dot and non-dot-like signals. First, nuclei are segmented from their background and from each other in order to associate signals with specific isolated nuclei. Second, subsignals composing non-dot-like signals are detected and clustered to signals. Features are measured to the signals and a subset of these features is selected representing the signals to a multiclass classifier. Classification using a naive Bayesian classifier (NBC) or a multilayer perceptron is accomplished. When applied to a FISH image database, dot and non-dot-like signals were segmented almost perfectly and then classified with accuracy of ~80% by either of the classifiers. View full abstract»

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  • Modeling of Entorhinal Cortex and Simulation of Epileptic Activity: Insights Into the Role of Inhibition-Related Parameters

    Page(s): 450 - 461
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1104 KB) |  | HTML iconHTML  

    This paper describes a macroscopic neurophysiologically relevant model of the entorhinal cortex (EC), a brain structure largely involved in human mesio-temporal lobe epilepsy. This model is intervalidated in the experimental framework of ictogenesis animal model (isolated guinea-pig brain perfused with bicuculline). Using sensitivity and stability analysis, an investigation of model parameters related to GABA neurotransmission (recognized to be involved in epileptic activity generation) was performed. Based on spectral and statistical features, simulated signals generated from the model for multiple GABAergic inhibition-related parameter values were classified into eight classes of activity. Simulated activities showed striking agreement (in terms of realism) with typical epileptic activities identified in field potential recordings performed in the experimental model. From this combined computational/experimental approach, hypotheses are suggested about the role of different types of GABAergic neurotransmission in the generation of epileptic activities in EC. View full abstract»

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  • TimeLine: Visualizing Integrated Patient Records

    Page(s): 462 - 473
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1136 KB) |  | HTML iconHTML  

    An increasing amount of data is now accrued in medical information systems; however, the organization of this data is still primarily driven by data source, and does not support the cognitive processes of physicians. As such, new methods to visualize patient medical records are becoming imperative in order to assist physicians with clinical tasks and medical decision-making. The TimeLine system is a problem-centric temporal visualization for medical data: information contained with medical records is reorganized around medical disease entities and conditions. Automatic construction of the TimeLine display from existing clinical repositories occurs in three steps: 1. data access, which uses an extensible Markup Language (XML) data representation to handle distributed, heterogeneous medical databases; 2. data mapping and reorganization, reformulating data into hierarchical, problem-centric views; and 3. data visualization, which renders the display to a target presentation platform. Leveraging past work, we describe the latter two components of the TimeLine system in this paper, and the issues surrounding the creation of medical problems lists and temporal visualization of medical data. A driving factor in the development of TimeLine was creating a foundation upon which new data types and the visualization metaphors could be readily incorporated. View full abstract»

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  • A Novel Surface Registration Algorithm With Biomedical Modeling Applications

    Page(s): 474 - 482
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (485 KB) |  | HTML iconHTML  

    In this paper, we propose a novel surface matching algorithm for arbitrarily shaped but simply connected 3-D objects. The spherical harmonic (SPHARM) method is used to describe these 3-D objects, and a novel surface registration approach is presented. The proposed technique is applied to various applications of medical image analysis. The results are compared with those using the traditional method, in which the first-order ellipsoid is used for establishing surface correspondence and aligning objects. In these applications, our surface alignment method is demonstrated to be more accurate and flexible than the traditional approach. This is due in large part to the fact that a new surface parameterization is generated by a shortcut that employs a useful rotational property of spherical harmonic basis functions for a fast implementation. In order to achieve a suitable computational speed for practical applications, we propose a fast alignment algorithm that improves computational complexity of the new surface registration method from O(n3) to O(n2). View full abstract»

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  • System for Infectious Disease Information Sharing and Analysis: Design and Evaluation

    Page(s): 483 - 492
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (451 KB) |  | HTML iconHTML  

    Motivated by the importance of infectious disease informatics (IDI) and the challenges to IDI system development and data sharing, we design and implement BioPortal, a Web-based IDI system that integrates cross-jurisdictional data to support information sharing, analysis, and visualization in public health. In this paper, we discuss general challenges in IDI, describe BioPortal's architecture and functionalities, and highlight encouraging evaluation results obtained from a controlled experiment that focused on analysis accuracy, task performance efficiency, user information satisfaction, system usability, usefulness, and ease of use. View full abstract»

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  • Co-clustering: A Versatile Tool for Data Analysis in Biomedical Informatics

    Page(s): 493 - 494
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (170 KB) |  | HTML iconHTML  

    Co-clustering has not been much exploited in biomedical informatics, despite its success in other domains. Most of the previous applications were limited to analyzing gene expression data. We performed co-clustering analysis on other types of data and obtained promising results, as summarized in this paper. View full abstract»

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  • 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'08)

    Page(s): 495
    Save to Project icon | Request Permissions | PDF file iconPDF (492 KB)  
    Freely Available from IEEE
  • Search for editor-in-chief for IEEE Transactions on NanoBioscience

    Page(s): 496
    Save to Project icon | Request Permissions | PDF file iconPDF (416 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Information Technology in Biomedicine Information for authors

    Page(s): C3
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    Freely Available from IEEE

Aims & Scope

The IEEE Transactions on Information Technology in Biomedicine publishes basic and applied papers of information technology applications in health, healthcare and biomedicine.

 

This Transaction ceased publication in 2012. The current retitled publication is IEEE Journal of Biomedical and Health Informatics.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Yuan-ting Zhang
427, Ho Sin Hang Engineering Building, The Chinese
University of Hong Kong, Shatin, NT, Hong Kong
ytzhang@ee.cuhk.edu.hk
Phone:+852 2609-8458
Fax:+852 2609-5558