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PubMed2002

A patient database application for Hereditary Deafness Epidemiology and Clinical Research (H.E.A.R.): an effort for standardization in multiple languages.

One of the most challenging and neglected issues in medicine is the effective recording of the data obtained from the patients. The "European Work Group on the Genetics of Hearing Impairment," which has been working since 1996, proposed a few questionnaires to collect data regarding the phenotype, ENT findings, audiological examination findings and other special investigations. In this study, a computerized patient database application named "Izmir H.E.A.R version 1.0," written in Delphi 4.0 for Windows for recording the patients with hearing problems, is presented. The application consists of a modular form, including information about identity, genetic condition, proband query, audiology and vestibular tests, phenotype, pedigree and special examinations, which allows data entry on all these issues. It has been developed by using the guidelines of Hereditary Deafness Epidemiology and Clinical Research (H.E.A.R.) and by the experience gained within the last 10 years by the authors. The target population of the program is the ENT clinicians, audiologists, epidemiologists, geneticists and researchers in the field. The main idea is to create a program serving the needs of both the daily routine work and research purposes and to distribute this program to the above-mentioned specialists, to encourage them to try the first version and to find a standard and/or better way to collect data. For this reason, the program aims to be multilingual, and the currently available languages are English, German, Spanish and Turkish.

Biomedical Research↗

PubMed2001

Managing predefined templates and macros for a departmental speech recognition system using common software.

The authors have developed a networked database system to create, store, and manage predefined radiology report definitions. This was prompted by complete departmental conversion to a computer speech recognition system (SRS) for clinical reporting. The software complements and extends the capabilities of the SRS, and 2 systems are integrated by means of a simple text file format and import/export functions within each program. This report describes the functional requirements, design considerations, and implementation details of the structured report management software. The database and its interface are designed to allow all radiologists and division managers to define and update template structures relevant to their practice areas. Two key conceptual extensions supported by the template management system are the addition of a template type construct and allowing individual radiologists to dynamically share common organ system or modality-specific templates. In addition, the template manager software enables specifying predefined report structures that can be triggered at the time of dictation from printed lists of barcodes. Initial experience using the program in a regional, multisite, academic radiology practice has been positive.

Computer Peripherals↗

PubMed2006

A comparative study of cells in inflammation, EAE and MS using biomedical literature data mining.

Biomedical literature and database annotations, available in electronic forms, contain a vast amount of knowledge resulting from global research. Users, attempting to utilize the current state-of-the-art research results are frequently overwhelmed by the volume of such information, making it difficult and time-consuming to locate the relevant knowledge. Literature mining, data mining, and domain specific knowledge integration techniques can be effectively used to provide a user-centric view of the information in a real-world biological problem setting. Bioinformatics tools that are based on real-world problems can provide varying levels of information content, bridging the gap between biomedical and bioinformatics research. We have developed a user-centric bioinformatics research tool, called BioMap, that can provide a customized, adaptive view of the information and knowledge space. BioMap was validated by using inflammatory diseases as a problem domain to identify and elucidate the associations among cells and cellular components involved in multiple sclerosis (MS) and its animal model, experimental allergic encephalomyelitis (EAE). The BioMap system was able to demonstrate the associations between cells directly excavated from biomedical literature for inflammation, EAE and MS. These association graphs followed the scale-free network behavior (average gamma = 2.1) that are commonly found in biological networks.

Animals↗

PubMedDate not supplied

Computer-assisted dynamic integration of multiple medical thesauruses.

We have previously described a user-interactive rule-based computer program (Dyna-SaurI) designed for dynamic thesaurus integration, and demonstrated its efficacy on integrating dermatological subsets of the MeSH and SNOMED thesauruses. In the present study, we have refined our rules for merging and mapping multiple thesauruses and tested these rules. We then applied them with a set of optimized parameters to the integration of a third thesaurus, a subset of the International Coding Index for Dermatology, with the Integrated MeSH-SNOMED thesaurus. The parameter changes resulted in improved ranking of more specific and conceptually closer terms.

Abstracting and Indexing↗

PubMed1995

Free text analysis.

In the context of hospital information systems (HIS) medical free text analysis is reviewed with respect to current automated approaches to literature retrieval, case retrieval and fact retrieval from textual data in the patient record. The Unified Medical Language System (UMLS) project has enormously stimulated current research. It is expected that UMLS knowledge sources and SNOMED III (which need a translation into other languages as soon as possible) as well as the conceptual graphs formalism, could become standards to utilize free text information contained in HIS databases.

Abstracting and Indexing↗

PubMed1994

The GALEN project.

The GALEN project is developing language independent concept representation systems as the foundations for the next generation of multilingual coding systems. It aims to support the flexibility required to cope with the diversity amongst medical applications, while ensuring the coherence necessary for integration and re-use of terminologies. GALEN is developing a fully compositional and generative formal system for modelling concepts: the GALEN Representation and Integration Language (GRAIL) Kernel. Its goal is to overcome many of the problems with traditional coding and classification systems, in particular the combinatorial explosion of terms in enumerative systems and the generation of nonsensical terms in partially compositional systems. It will also provide a clean separation between the concept model and linguistic mechanisms which interpret that model (i.e., the words in a specific language, syntax, alternative phrasings, etc.) in order to allow the development of multilingual systems. GRAIL aims to be formally sound and produce models that are verifiable and contain no contradictions or ambiguities, with realistic human effort. A Coding Reference (CORE) Model of medical terminology covering is being developed which aims to represent the core concepts in for example pathology, anatomy and therapeutics, that have widespread applicability in medical applications. It should also provide the basis for specialist extensions according to the formal principles of GRAIL. The main results of GALEN will be delivered as a Terminology Server (TeS) which encapsulates and coordinates the functionality of the concept module, multilingual module, and code conversion module, and also provides a uniform applications programming interface and network services for use by external applications.

Databases, Bibliographic↗

PubMed1994

MENELAS: an access system for medical records using natural language.

The overall goal of MENELAS is to provide better access to the information contained in natural language patient discharge summaries, through the design and implementation of a pilot system able to access medical reports through natural languages. A first, experimental version of the MENELAS indexing prototype for French has been assembled. Its function is to encode free text PDSs into both an internal representation and ICD-9-CM nomenclature codes. A preliminary evaluation shows the potential for reasonable coverage and precision. The MENELAS prototype will be enhanced and extended into a pilot system which will be tested in two hospital sites.

Abstracting and Indexing↗

PubMed1995

Computerized measurement of the content analysis of natural language for use in biomedical and neuropsychiatric research.

Over several decades, the senior author, with various colleagues, has developed an objective method of measuring the magnitude of commonly useful and pertinent neuropsychiatric and neuropsychological dimensions from the content and form analysis of verbal behavior and natural language. Extensive reliability and validation studies using this method have been published involving English, German, Spanish and many other languages, and which confirm that these Content Analysis Scales can be reliably scored cross-culturally and have construct validity. The validated measures include the Anxiety Scale (and six subscales), the Hostility Outward Scale (and two subscales), the Hostility In Scale, the Ambivalent Hostility Scale, the Social Alienation-Personal Disorganization Scale, the Cognitive Impairment Scale, the Depression Scale (and seven subscales), and the Hope Scale. Here, the authors report the development of artificial intelligence (LISP based) software that can reliably score these Content Analysis Scales, whose achievement facilitates the application of these measures to biomedical and neuropsychiatric research.

Diagnosis, Computer-Assisted↗

PubMed1995

An intelligent interactive system for delivering individualized information to patients.

This paper is a report on the first phase of a long-term, interdisciplinary project whose goal is to increase the overall effectiveness of physicians' time, and thus the quality of health care, by improving the information exchange between physicians and patients in clinical settings. We are focusing on patients with long-term and chronic conditions, initially on migraine patients, who require periodic interaction with their physicians for effective management of their condition. We are using medical informatics to focus on the information needs of patients, as well as of physicians, and to address problems of information exchange. This requires understanding patients' concerns to design an appropriate system, and using state-of-the-art artificial intelligence techniques to build an interactive explanation system. In contrast to many other knowledge-based systems, our system's design is based on empirical data on actual information needs. We used ethnographic techniques to observe explanations actually given in clinic settings, and to conduct interviews with migraine sufferers and physicians. Our system has an extensive knowledge base that contains both general medical terminology and specific knowledge about migraine, such as common trigger factors and symptoms of migraine, the common therapies, and the most common effects and side effects of those therapies. The system consists of two main components: (a) an interactive history-taking module that collects information from patients prior to each visit, builds a patient model, and summarizes the patients' status for their physicians; and (b) an intelligent explanation module that produces an interactive information sheet containing explanations in everyday language that are tailored to individual patients, and responds intelligently to follow-up questions about topics covered in the information sheet.

Anthropology, Cultural↗

PubMed1996

Generating recipient-centered explanations about drug prescription.

In this paper we describe how we generated written explanations to 'indirect users' of a knowledge-based system in the domain of drug prescription. We call 'indirect users' the intended recipients of explanations, to distinguish them from the prescriber (the 'direct' user) who interacts with the system. The Explanation Generator was designed after several studies about indirect users' information needs and physicians' explanatory attitude in this domain. It integrates text planning techniques with ATN-based surface generation. A double modeling component enables adapting the information content, order and style to the indirect user to whom explanation is addressed. Several examples of computer-generated texts are provided, and they are contrasted with the physicians' explanations to discuss advantages and limits of the approach adopted.

Drug Information Services↗

PubMed2005

Use of computerized surveillance to detect nosocomial pneumonia in neonatal intensive care unit patients.

BACKGROUND: Pneumonia surveillance is difficult and time-consuming. The definition is complicated, and there are many opportunities for subjectivity in determining infection status. OBJECTIVE: To compare traditional infection control professional (ICP) surveillance for pneumonia among neonatal intensive care unit (NICU) patients with computerized surveillance of chest x-ray reports using an automated detection system based on a natural language processor. METHODS: This system evaluated chest x-rays from 2 NICUs over a 2-year period. It flagged x-rays indicative of pneumonia according to rules derived from the National Nosocomial Infection Surveillance System definition as applied to radiology reports. Data from the automated system were compared with pneumonia data collected prospectively by an ICP. RESULTS: Sensitivity of the computerized surveillance in NICU 1 was 71%, and specificity was 99.8%. The positive predictive value was 7.9%, and the negative predictive value (NPV) was >99%. Data from NICU 2 were incomplete. CONCLUSIONS: Computer-assisted surveillance has the potential to decrease ICP workload and make pneumonia surveillance feasible. The high NPV means the system can safely screen out many chest x-rays of noninfected patients. However, all data must be available to the computer system and must be analyzed the same way for results to be comparable.

Computers↗

PubMed2004

Searching information with a natural language dialogue system: a comparison of spoken vs. written modalities.

This paper examines the effects of spoken vs. written dialogue modalities on the effectiveness of information search with a computerized retrieval system. Forty-eight adults familiar with the use of computers were asked to carry out six information retrieval tasks, engaging with the system using either spoken or written communication. The written modality was more efficient with regard to the number of dialogue turns, length of interaction with the system and mental workload. Even though the turns lasted longer in the written mode, they appeared to yield less mental workload. Moreover, spoken and written dialogues did not differ as regards the use of pronouns and articles. The implications for the development of natural-language dialogue systems are discussed.

Adolescent↗

PubMed2005

Part-whole representation and reasoning in formal biomedical ontologies.

OBJECTIVE: Biomedical ontologies are typically structured in a biaxial way, reflecting both a taxonomic (is-a) and a partonomic (part-of) hierarchy. Commonly used biomedical terminologies, which incorporate such distinctions excel in terms of broad coverage but lack a rigid formal foundation. The latter, however, is a prerequisite for automated reasoning. For the biomedical domain, it is not only crucial to cope with ontological dependencies between wholes and their parts but also with specific reasoning patterns which underlie the propagation of roles across partonomic hierarchies. METHODS: We scale down part-whole reasoning to subsumption-based taxonomic reasoning within the formal framework of a parsimonious variant of description logics (viz. ALC). RESULTS: We provide a formal basis for ontological engineering in the domain of biomedicine, as far as part-whole relationships are concerned, by addressing typical reasoning patterns encountered in this domain.

Artificial Intelligence↗

PubMedDate not supplied

Multiset splicing systems.

We consider splicing systems reflecting two important aspects of the behaviour of DNA molecules in nature or in laboratory experiments which so far have not been studied in the literature. We examine the effect of splicing rules applied to finite multisets of words using sequential and different types of parallel derivation strategies and compare the sets of words or sets of multisets which can be obtained.

DNA↗

PubMed2006

When language breaks into pieces. A conflict between communication through isolated signals and language.

Here, we study a communication model where signals associate to stimuli. The model assumes that signals follow Zipf's law and the exponent of the law depends on a balance between maximizing the information transfer and saving the cost of signal use. We study the effect of tuning that balance on the structure of signal-stimulus associations. The model starts from two recent results. First, the exponent grows as the weight of information transfer increases. Second, a rudimentary form of language is obtained when the network of signal-stimulus associations is almost connected. Here, we show the existence of a sudden destruction of language once a critical balance is crossed. The model shows that maximizing the information transfer through isolated signals and language are in conflict. The model proposes a strong reason for not finding large exponents in complex communication systems: language is in danger. Besides, the findings suggest that human words may need to be ambiguous to keep language alive. Interestingly, the model predicts that large exponents should be associated to decreased synaptic density. It is not surprising that the largest exponents correspond to schizophrenic patients since, according to the spirit of Feinberg's hypothesis, i.e. decreased synaptic density may lead to schizophrenia. Our findings suggest that the exponent of Zipf's law is intimately related to language and that it could be used to detect anomalous structure and organization of the brain.

Animals↗

PubMed2005

A graphic tool for curating molecular interaction networks from the literature.

We propose a graphic tool for curating molecular interaction networks constructed from the literature by information extraction (IE). In order to turn preliminary results from IE into useful biomedical resources, we propose to use a controlled environment in which visualization and IE work synergistically. The usability of the proposed graphic tool is shown with respect to the identification of incorrectly extracted results that are due to the much troubling coordination phenomena in natural language texts. Through the experiment on molecular interactions in Saccaharomyces cerevisiae, we have seen a meaningful increase (from 91.5% to 97.5%) in the number of correctly extracted interaction information.

Computational Biology↗

PubMed2005

Assessment of approximate string matching in a biomedical text retrieval problem.

Text-based search is widely used for biomedical data mining and knowledge discovery. Character errors in literatures affect the accuracy of data mining. Methods for solving this problem are being explored. This work tests the usefulness of the Smith-Waterman algorithm with affine gap penalty as a method for biomedical literature retrieval. Names of medicinal herbs collected from herbal medicine literatures are matched with those from medicinal chemistry literatures by using this algorithm at different string identity levels (80-100%). The optimum performance is at string identity of 88%, at which the recall and precision are 96.9% and 97.3%, respectively. Our study suggests that the Smith-Waterman algorithm is useful for improving the success rate of biomedical text retrieval.

Algorithms↗

PubMed2005

Automatic generation of repeated patient information for tailoring clinical notes.

Generating clear, readable, and accurate reports can be a time-consuming task for physicians. Clinical notes, which document patient encounters, often contain a certain set of patient information including demographics, medical history, surgical history, examination results or the current medical condition that is propagated from one clinical note to all subsequent clinical notes for the same patient. To this end, we present a system, which automatically generates this patient information for the creation of a new clinical note. We use semantic patterns and an approximate sequence matching algorithm for capturing the discourse role of sentences, which we show to be a useful feature for determining whether the sentence should be repeated. Our system is shown to perform better than a simple baseline metric using precision/recall results. We believe such a system would allow clinical notes to be more complete, timely, and accurate.

Documentation↗