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Results for “information extraction”

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At least 19 recordsLinked to original sources

PubMed2004

[Using wavelet transform for information extraction from remote sensing FTIR spectra].

How to use wavelet transform technology to extract information from remote sensing FTIR spectra, which were weak or always interfered by others, was described in the present paper. The Mexican hat function was used as a wavelet function to continuously transform the signals of pure chloroform, pure acetone and their mixture. The results indicated that the small scales were the guarantee of the accuracy of corresponding position between maximum module of wavelet transform coefficients and break points of peaks. However, only one scale could not determine the position of break point because of the effect of noise in small scales. On the contrary, maximum module of wavelet transform coefficients was relatively stable in large scales when noise was smoothed. But smoothness always brought deviation of orientation. Therefore, multi-scales should be combined to observe the break points of signals when using wavelet transform technology. All in all, the break points of signals could be determined accurately and stably by the wavelet transform technology and useful information was extracted. The signals were smoothed and magnified at the same time. According to the analysis of maximum module of wavelet transform coefficients and their orientation in different scales, some spectra, such as mixed and non-strongly-overlapped remote sensing FTIR spectra, could be recognized magnificently.

English Abstract↗

PubMedDate not supplied

Application of four-layer neural network on information extraction.

This paper applies neural network to extract marsh information. An adaptive back-propagation algorithm based on a robust error function is introduced to build a four-layer neural network, and it is used to classify Thematic Mapper (TM) image of Zhalong Wetland in China and then extract marsh information. Comparing marsh information extraction results of the four-layer neural network with three-layer neural network and the maximum likelihood classifier, conclusion can be drawn as follows: the structure of the four-layer neural network and the adaptive back-propagation algorithm based on the robust error function is effective to extract marsh information. The four-layer neural network adopted in this paper succeeded in building the complex model of TM image, and it avoided the problem of great storage of remotely sensed data, and the adaptive back-propagation algorithm speeded up the descending of error. Above all, the four-layer neural network is superior to the three-layer neural network and the maximum likelihood classifier in the accuracy of the total classification and marsh information extraction.

Algorithms↗

PubMed2002

NLP-based information extraction for managing the molecular biology literature.

We present research aimed at devising a tool for using natural language processing to identify and extract biomedical information from text for the purpose of assisting researchers in molecular biology manage large amounts of information. A pilot project based on the molecular genetics of diabetes demonstrates our ability to explore the interaction of genomic phenomena and clinical findings. We suggest the cooperation of this extracted information with systems for clustering text and constructing labeled networks of data.

Diabetes Mellitus↗

PubMed2000

Two applications of information extraction to biological science journal articles: enzyme interactions and protein structures.

Information extraction technology, as defined and developed through the U.S. DARPA Message Understanding Conferences (MUCs), has proved successful at extracting information primarily from newswire texts and primarily in domains concerned with human activity. In this paper we consider the application of this technology to the extraction of information from scientific journal papers in the area of molecular biology. In particular, we describe how an information extraction system designed to participate in the MUC exercises has been modified for two bioinformatics applications: EMPathIE, concerned with enzyme and metabolic pathways; and PASTA, concerned with protein structure. Progress to date provides convincing grounds for believing that IE techniques will deliver novel and effective ways for scientists to make use of the core literature which defines their disciplines.

Binding Sites↗

PubMed1987

Auditory sensory storage in relation to the growth of sensation and acoustic information extraction.

A brief, vivid phase of auditory sensory storage that outlasts the stimulus could be used in perception in two ways: First, all of the neural activity resulting from the stimulus, including that of the sensory store, could contribute to a sensation of growing loudness; second, the sensory store could permit the continued extraction of information about the sound's acoustic properties. This study includes a task for which these two processes lead to different predictions; a third prediction is based on the two processes combined. The task required loudness judgments for two brief tones presented with a variable intertone interval. The results of Experiments 1-3 were as one would expect if both the growth of sensation and information extraction contributed to the pattern of loudness judgments. Experiment 4 strengthened the two-process account by demonstrating the separability of the two processes. Approaches to mathematical modeling of these results are discussed.

Adult↗

PubMed1998

Developing NLP Tools for Genome Informatics: An Information Extraction Perspective.

Huge quantities of on-line medical texts such as Medline are available, and we would hope to extract useful information from these resources, as much as possible, hopefully in an automatic way, with the aid of computer technologies. Especially, recent advances in Natural Language Processing (NLP) techniques raise new challenges and opportunities for tackling genome-related on-line text; combining NLP techniques with genome informatics extends beyond the traditional realms of either technology to a variety of emerging applications. In this paper, we explain some of our current efforts for developing various NLP-based tools for tackling genome-related on-line documents for information extraction task.

Journal Article↗

PubMed2002

Information extraction from biomedical text.

Information extraction is the process of scanning text for information relevant to some interest, including extracting entities, relations, and events. It requires deeper analysis than key word searches, but its aims fall short of the very hard and long-term problem of full text understanding. Information extraction represents a midpoint on this spectrum, where the aim is to capture structured information without sacrificing feasibility. One of the key ideas in this technology is to separate processing into several stages, in cascaded finite-state transducers. The earlier stages recognize smaller linguistic objects and work in a largely domain-independent fashion. The later stages take these linguistic objects as input and find domain-dependent patterns among them. There are now initial efforts to apply this technology to biomedical text. In other domains, the technology plateaued at about 60% recall and precision. Even if applications to biomedical text do no better than this, they could still prove to be of immense help to curatorial activities.

Abstracting and Indexing↗

PubMed2002

Information extraction in molecular biology.

Information extraction has become a very active field in bioinformatics recently and a number of interesting papers have been published. Most of the efforts have been concentrated on a few specific problems, such as the detection of protein-protein interactions and the analysis of DNA expression arrays, although it is obvious that there are many other interesting areas of potential application (document retrieval, protein functional description, and detection of disease-related genes to name a few). Paradoxically, these exciting developments have not yet crystallised into general agreement on a set of standard evaluation criteria, such as the ones developed in fields such as protein structure prediction, which makes it very difficult to compare performance across these different systems. In this review we introduce the general field of information extraction, we outline the status of the applications in molecular biology, and we then discuss some ideas about possible standards for evaluation that are needed for the future development of the field.

Information Management↗

PubMed2004

An architecture for biological information extraction and representation.

MOTIVATIONS: Technological advances in biomedical research are generating a plethora of heterogeneous data at a high rate. There is a critical need for extraction, integration and management tools for information discovery and synthesis from these heterogeneous data. RESULTS: In this paper, we present a general architecture, called ALFA, for information extraction and representation from diverse biological data. The ALFA architecture consists of: (i) a networked, hierarchical, hyper-graph object model for representing information from heterogeneous data sources in a standardized, structured format; and (ii) a suite of integrated, interactive software tools for information extraction and representation from diverse biological data sources. As part of our research efforts to explore this space, we have currently prototyped the ALFA object model and a set of interactive software tools for searching, filtering, and extracting information from scientific text. In particular, we describe BioFerret, a meta-search tool for searching and filtering relevant information from the web, and ALFA Text Viewer, an interactive tool for user-guided extraction, disambiguation, and representation of information from scientific text. We further demonstrate the potential of our tools in integrating the extracted information with experimental data and diagrammatic biological models via the common underlying ALFA representation. CONTACT: aditya_vailaya@agilent.com.

Abstracting and Indexing↗

PubMed2005

Information extraction in the life sciences: perspectives for medicinal chemistry, pharmacology and toxicology.

Information extraction approaches have been successfully applied to mine the scientific literature in biology and medicine. So far, the main focus of research and development in this domain was on the recognition and extraction of gene and protein names in the context of molecular biology and genome research and on disease names and other medical terms in the context of clinical research. Similar to biology and medical sciences, medicinal chemistry, pharmacology and toxicology are descriptive sciences. However, information extraction approaches in these disciplines encounter a number of problems that are specific to the fact that these scientific areas are essentially centred at chemical compounds and their structures. In this review, we will give a short overview on general information extraction strategies in the life sciences and we will introduce new approaches to apply information extraction to the domain of pharmacology, medicinal chemistry and toxicology. Finally, we will emphasize on how information extraction approaches will support public and commercial research in medicinal chemistry, pharmacology and toxicology by linking information on chemical structures to biological information.

Biological Science Disciplines↗

PubMed2004

Chemical documents: machine understanding and automated information extraction.

Automatically extracting chemical information from documents is a challenging task, but an essential one for dealing with the vast quantity of data that is available. The task is least difficult for structured documents, such as chemistry department web pages or the output of computational chemistry programs, but requires increasingly sophisticated approaches for less structured documents, such as chemical papers. The identification of key units of information, such as chemical names, makes the extraction of useful information from unstructured documents possible.

Chemistry↗

PubMed2006

MedIEQ-Quality labelling of medical web content using multilingual information extraction.

Quality of Internet health information is essential because it has the potential to benefit or harm a large number of people and it is therefore essential to provide consumers with some tools to aid them in assessing the nature of the information they are accessing and how they should use it without jeopardizing their relationship with their doctor. Organizations around the world are working on establishing standards of quality in the accreditation of health-related web content. For the full success of these initiatives, they must be equipped with technologies that enable the automation of the rating process and allow the continuous monitoring of labelled web sites alerting the labelling agency. In this paper we describe the European project MedIEQ (Quality Labelling of Medical Web Content Using Multilingual Information Extraction) that integrates the efforts of relevant organizations on medical quality labelling, multilingual information retrieval and extraction and semantic resources, from six different European countries (Spain, Germany, Greece, Finland, Czech Republic and Switzerland). The main objectives of MedIEQ are: first, to develop a scheme for the quality labelling of medical web content and provide the tools supporting the creation, maintenance and access of labelling data according to this scheme and second, to specify a methodology for the content analysis of medical web sites according to the MedIEQ scheme and develop the tools that will implement it.

Accreditation↗

PubMed2000

A pragmatic information extraction strategy for gathering data on genetic interactions.

We present in this paper a pragmatic strategy to perform information extraction from biologic texts. Since the emergence of the information extraction field, techniques have evolved, become more robust and proved their efficiency on specific domains. We are using a combination of existing linguistic and knowledge processing tools to automatically extract information about gene interactions in the literature. Our ultimate goal is to build a network of gene interactions. The methodologies used and the current results are discussed in this paper.

Animals↗

PubMed1994

Event-related potentials indicate information extraction in a comparative judgement task.

Event-related potentials (ERPs) were recorded from normal subjects in a serial paired-comparison task with the spoken digits one to five. For each digit, the subject decided whether it was smaller or larger than the preceding one. We examined to what extent ERP components are associated with the probability information each digit provides with respect to the subsequent response. Shortest reaction time (RT) and highest accuracy was obtained for the two end terms one and five. The N1 and P2 components of the ERP were attenuated for the two end terms. Three late positivities were found: early P3, P3b, and slow wave. P3b increased in amplitude the more information the eliciting digit provided with respect to the response to the subsequent digit. Moreover, a negative correlation was found between the P3b amplitude associated with information extraction and the RTs to the subsequent digit. During comparative judgement, subjects process the relative position of a stimulus within a stimulus set to extract information about the probability of a forthcoming response, and this process is reflected in P3b amplitude.

Adult↗

PubMed1988

A microcomputer-based algorithm for digitized image simplification and information extraction.

Spatial analysis of objects often requires significant image simplification prior to information extraction and application of a decision-making algorithm. Much decision making based on images (e.g., histologic diagnoses) requires identifying patterns in complex backgrounds (image simplification) and comparison of those patterns to other patterns (decision making). Automated extraction of information from images commonly requires the extraction system to recognize edges (contours) of structures and their internal discontinuities (such as gradations in density) and to selectively suppress irrelevant data in order to conserve memory and speed computation; data from homogeneous image areas occupy memory, but are noncontributory or redundant. This paper describes the development of a microcomputer-based algorithm that deletes all homogeneous information from overlaid digitized images, generating contours in the place of nonhomogeneities. Contours corresponding to different areas or objects depend on color differences between an object and its surroundings. Any set of contours can be deleted almost instantaneously, leaving only those of interest. Contours can be highlighted by an operator-driven interactive process if desired and can be deleted and retrieved until an appropriate image is obtained. This contour-generating and image-simplification algorithm facilitates three-dimensional reconstruction of an object from serial images by reducing the number of calculations required and yielding a cleaner final image.

Algorithms↗

PubMed1998

Vibrational Information Extracted from Inertial Defects: The Complete General Valence Force Field for 1,1-Difluoroethene

The method of extracting harmonic information from inertial defect differences has been used to obtain sufficient information for a determination of the complete force field for 1,1-difluoroethylene. The presumption that inertial defect differences for non-totally-symmetric vibrations of orthorhombic molecules contain purely harmonic information (1992. D. Christen, J. Mol. Spectrosc. 151, 1-11) must be revoked, however. Copyright 1998 Academic Press. Copyright 1998Academic Press

Journal Article↗

PubMed1998

Detecting Gene Symbols and Names in Biological Texts: A First Step toward Pertinent Information Extraction.

Gathering data on molecular interactions to be fed into a specialized database has motivated the development of a computer system to help extracting pertinent information from texts, relying on advanced linguistic tools, completed with object-oriented knowledge modeling capabilities. As a first step toward this challenging objective, a program for the identification of gene symbols and names inside sentences has been devised. The main difficulty is that these names and symbols do not appear to follow construction rules. The program is thus made up of a series of sieves of different natures, lexical, morphological and semantic, to distinguish among the words of a sentence those which can only be potential gene symbols or names. Its performance has been evaluated, in terms of coverage and precision ratios, on a corpus of texts concerning D. melanogaster for which the list of names of known genes is available for checking.

Journal Article↗

PubMed2002

Patient information extraction in digitized radiography.

Digital imagery is gradually replacing the traditional radiograph with the development of digital radiography and film scanner. This report presents a new method to extract the patient information number (PIN) field automatically from the film-scanned image using image analysis technique. To evaluate the PIN field extraction algorithm, 2 formats of label acquired from 2 different hospitals are tested. Given the available films with no constraints on the way the labels are written and positioned, the correct extraction rates are 73% and 84%, respectively. This extracted PIN information can link with Radiology Information System (RIS) or Hospital Information System (HIS), and the image scanned from the film then can be filed into the database automatically. The efficiency this method offers can simplify greatly the image filing process and improve the user friendliness of the overall image digitization system. Moreover, compared with the bar code reader, it solves the automatic information input problem in a very economical way. The authors believe the success of this technique will benefit the development of the PACS (Picture Archiving and Communication System) and teleradiology.

Algorithms↗