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PubMed1986

Electroencephalographic findings in unmedicated, neurologically and intellectually intact Tourette syndrome patients.

Electroencephalograms were obtained in 30 unmedicated, neurologically and intellectually intact Tourette syndrome (TS) patients, none having a history of clinically apparent seizure disorder. Six (20%) of initial 30 EEGs were judged to be abnormal, 2 (6.6%) on account of slowing of intrinsic rhythms and/or excess of slow frequencies and 4 (13.3%) on account of epileptiform alterations. Two of the latter 4 patients continued to show similar abnormalities in EEGs done 4 and 8 months later. Five of 6 patients with abnormal EEGs had history of migraine or migraine equivalents compared to 8 of 24 with normal EEGs (chi 2 = 4.88, P less than 0.05). It is concluded that in the population of Tourette patients studied, EEG abnormalities occurred in one-fifth of all patients despite an absence of medication effect, brain damage or seizure disorder and may, in part at least, be related to associated migrainous equivalents.

Adolescent↗
PubMed1975

Hypothesis processing as a new tool to aid managers of mental health agencies in serving long-term regional interests.

Mental health planning is partly a political process, involving the articulation of the long-range interests of a regional community, formation of consensus among key people and the appropriate investment of authority, power and responsibility. Conflicts between the short-term self-interests of planners and the long-term general interest usually arise. This paper claims that it is feasible to increase the expected number of cases in which a region's longer-term interest is served without radical changes in existing planning processes or ideologies. The means for doing this are new kinds of information systems that serve planners as tools to increase their awareness about assumptions, hypotheses and problem representations. The conceptual and technological bases for developing such systems stem from progress in artificial intelligence in the direction of hypothesis-processing algorithms. The proposed application to mental health planning is described. Arguments are presented to show how the use of such tools would increase the likelihood that longer-term regional interest are served.

Community Mental Health Services↗
PubMed1995

Mapping clause of Arden Syntax with HL7 and ASTM E 1238-88 standard.

The Arden Syntax is a standard description syntax for modular medical knowledge. The purpose of the Arden Syntax is to allow the construction of medical knowledge bases out of elementary medical logic modules (MLMs) that may be contributed and shared by different institutions. The format of the input data is not defined in the Arden Syntax, but left to the user. Every input and output must be rewritten for the local data access definition before an MLM can be used. It is suggested that by using the Health Level Seven (HL7) interface definition to define the communication and data transfer between the MLMs and the medical data base the shareability of MLMs can be enhanced.

Artificial Intelligence↗
PubMed1996

A Dutch medical language processor.

This paper describes the current state of a medical language processor for Dutch. The goal is to implement a language specific front-end compatible with some existing applications that aim at the intelligent extraction and processing of information from patient discharge summaries. A complete chain for processing and understanding Dutch medical documents will be the ultimate result. The text focuses mainly on the language specific aspects of the language processing chain. Evaluation results of the already functioning components are given as well as an outline for future developments and enhancements. A short theoretical background is provided (cf. also [1-3]: Rossi Mori et al., Proc. SCAMC 90, 1990, pp. 185-189; Wingert, in: Informatics and Medicine, an advanced course, Springer-Verlag. 1977, pp. 579-646; Wingert, Proc. MEDINFO 80, 1980, pp. 1321-1331) before the description of each component in order to familiarise the non-experienced reader with the basic notions of computational linguistics.

Artificial Intelligence↗
PubMed1993

The effect of mode of delivery on long-term outcome of very low birthweight infants.

A prospective 2-year neurodevelopmental follow-up was carried out on 69 very low birthweight (VLBW) infants (< 1501 g), born in the years 1985-87. The aim of the study was to determine whether there was a long-term advantage to cesarean section in these infants. The incidence of major disability and cognitive ability at 2 years of age were assessed, comparing modes of delivery. Cesarean section was performed in 38 out of 69 (55.1%) of the infants. Major disability was diagnosed in 11/69 (15.9%) of the children, of whom 7/38 (18.4%) were delivered by cesarean section, compared with 4/31 (12.9%) delivered vaginally. The difference, accounting for presentation and multiple birth was not statistically significant. Cognitive ability at 2 years of age was tested using the Mental Development Index (MDI) of the Bayley Scales, and was compared, according to mode of delivery, in 55 of 58 infants without major disability. There was no statistically significant difference between mean +/- S.E. in the MDI of 28 infants delivered by cesarean section (99.7 +/- 7.3) and that of 27 infants delivered vaginally (95.6 +/- 4). In summary, at 2 years of age, no clinically relevant benefit was found for VLBW infants who had been delivered by cesarean section.

Blindness↗
PubMedDate not supplied

Long-term consequences of CNS treatment for childhood cancer, Part II: Clinical consequences.

Survival of children with brain tumors has improved over the past 20 years due in part to advances in surgery, radiation, and most recently chemotherapy. The long-term adverse effects of radiation and chemotherapy on these children is the subject of this report. In Part I, we reviewed the pathologic consequences of radiation, including leukoencephalopathy, radiation necrosis, and radiation myelopathy as well as the oncogenic effects of both radiation and chemotherapy. Part II addresses the long-term consequences of radiation and chemotherapy on intellectual and endocrine function. Risk factors for the development of both endocrinopathies and intellectual dysfunction include age at the time of radiation, volume and dose of radiation, site of tumor, and use of adjuvant chemotherapy, in particular methotrexate. Early recognition of these complications and treatment, where indicated, will measurably improve the quality-of-life of children treated for brain tumors. The national cancer groups are currently attempting to limit these long-term adverse effects by taking risk factors into account when formulating new treatment regimens.

Brain Neoplasms↗
PubMed1994

Refinement of the HEPAR expert system: tools and techniques.

Methods and tools for the static and dynamic verification and validation of software systems are commonplace in the field of software engineering. In the field of expert systems, where it is more difficult to ensure that a system meets the specifications and expectations than in traditional software engineering, such tools are generally not available. In this paper, the need for more support of the development process by methods and tools is illustrated by the approach taken in building the HEPAR system, a rule-based expert system that can be used as a supportive tool in the diagnosis of disorders of the liver and biliary tract. At a certain stage in the development of this system an incremental development methodology has been adopted, in which implementation of parts of the expert system was followed by dynamic validation. For this purpose, a collection of software tools were implemented as extensions to a rule-based expert-system shell. These tools provide valuable information about the effects of modification of the HEPAR knowledge base, and indicate places in the knowledge base for refinement. It is believed that similar software tools may prove helpful in the development of other expert systems as well.

Artificial Intelligence↗
PubMed1994

Finding temporal patterns--a set-based approach.

We created an inference engine and query language for expressing temporal patterns in data. The patterns are represented by using temporally-ordered sets of data objects. Patterns are elaborated by reference to new objects inferred from original data, and by interlocking temporal and other relationships among sets of these objects. We found the tools well-suited to define scenarios of events that are evidence of inappropriate use of prescription drugs, using Medicaid administrative data that describe medical events. The tools' usefulness in research might be considerably more general.

Artificial Intelligence↗
PubMed1996

Introducing spatio-temporal reasoning into the inverse problem in electroencephalography.

Studying the Brain's Electrical and Magnetic Signals (BEMS) requires the contribution of many area of research that include anatomy, neurophysiology and electromagnetic theory. NEUROLAB is a framework dedicated to the study of brain disorders. Upon completion, it should provide users with an intelligent computational environment that incorporates qualitative and quantitative models of the brain and head, and a model for representing and reasoning about time and space. Spatio-temporal knowledge of a given problem is represented as a constraint network where to each node of the network are attached temporal and spatial variables that must satisfy the constraints defined by the arch labels connecting the nodes. In this paper, we show how temporal reasoning can be combined with spatial descriptions to produce different scenarios of possible seizure spread. These scenarios can provide a priori information for the inverse problem the role of which is to localise the sources of the observed BEMS.

Artificial Intelligence↗
PubMed2005

A hybrid method for relation extraction from biomedical literature.

PURPOSE: Over recent years, there has been a growing interest in extracting entities and relations from biomedical literature. There are a vast number of systems and approaches being proposed to extract biological relations, but none of them achieves satisfactory results. These methodologies are either parsing-based or pattern-based, which are not competent to handle the grammatical complexities of biomedical texts, or too complicated to be adapted. It is well known that appositive, coordinative propositions and such grammatical structures are extremely common in biomedical texts, particularly in full texts. However, these problems are still untouched for most of researchers. METHODS: In this paper, we have proposed a new approach, which is hybrid with both shallow parsing and pattern matching, to extract relations between proteins from scientific papers of biomedical themes. In the method, appositive and coordinative structures are interpreted based on the shallow parsing analysis, with both syntactic and semantic constraints. Then long sentences are splitted into sub-ones, from which relations are extracted by a greedy pattern matching algorithm, along with automatically generated patterns. RESULTS: Our approach is experimented to extract protein-protein interactions from full biomedical texts, and has achieved an average F-score of 80% on individual verbs, and 66% on all verbs. With the help of shallow parsing analysis, pattern matching is improved remarkably. Compared with the traditional pattern matching algorithm, our approach achieves about 7% improvement of both precision and F-score. In contrast to other systems, our approach achieves performance comparable to the best. A demo system has been available at http://spies.cs.tsinghua.edu.cn.

Abstracting and Indexing↗
PubMed2004

Methods for automated concept mapping between medical databases.

The retrieval and exchange of information between medical databases is often impeded by the semantic heterogeneity of concepts contained within the databases. Manual identification of equivalent database elements consumes time and resources, and may often be the rate-limiting technological step in integrating disparate data sources. By employing semantic networks as an intermediary representation of the native databases, automated mapping algorithms can identify equivalent concepts in disparate databases. The algorithms take advantage of the conceptual "context" embodied within a semantic network to produce candidate concept mappings. The performance of automated concept mapping was evaluated by creating semantic network representations for two test laboratory databases. The mapping algorithms identified all equivalent concepts that were present in the databases, and did not leave any equivalent concepts unmapped. The utilization of conceptual context to perform automated concept mapping facilitates the identification of equivalent database concepts and may help decrease the work and costs associated with retrieval and integration of information from disparate databases.

Algorithms↗
PubMed2005

Knowledge guided analysis of microarray data.

To microarray expression data analysis, it is well accepted that biological knowledge-guided clustering techniques show more advantages than pure mathematical techniques. In this paper, Gene Ontology is introduced to guide the clustering process, and thus a new algorithm capturing both expression pattern similarities and biological function similarities is developed. Our algorithm was validated on two well-known public data sets and the results were compared with some previous works. It is shown that our method has advantages in both the quality of clusters and the precision of biological annotations. Furthermore, the clustering results can be adjusted according to different stringency requirements. It is expected that our algorithm can be extended to other biological knowledge, for example, metabolic networks.

Algorithms↗
PubMed2005

ECGScan: a method for conversion of paper electrocardiographic printouts to digital electrocardiographic files.

BACKGROUND: Measurements of parameters from electrocardiograms (ECGs) are still largely performed from paper ECG records. Recent guidelines from regulatory agencies and, in particular, the requirement of the Food and Drug Administration to enforce the digital submission of annotated ECGs have triggered significant efforts in the pharmaceutical industry, which, to comply with the new guidelines, is adopting digital ECG technology. At the same time, the new requirements justify the need for tools to convert existing paper ECG records into digital format, particularly for retrospective studies. METHODS: This article presents ECGScan, a computer application developed for the conversion of paper ECG records to digital ECG files. An image processing engine is used to first detect the underlying grid and, subsequently, to extrapolate the ECG waveforms using a technique based on active contour modeling. RESULTS: ECGScan was validated using a set of 60 ECGs for which both the original digital waveform and paper printouts were available. Sample-by-sample comparisons provided evidence of a robust wave reconstruction (root mean square value from 169 PQRST complexes was 16.8+/-11.8 microV). Semiautomatic measurements of QT intervals performed on 144 complexes also indicated a strong agreement between original and derived ECGs (DeltaQT=0.577+/-5.41 milliseconds). CONCLUSIONS: ECGScan provides a robust reconstruction of a digital ECG, both in waveform reconstruction and in QT measurements performed on original (digital) ECGs and on digitized ECGs from paper printouts.

Artificial Intelligence↗