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PubMed1998

A Knowledge-Based Systems Approach to Design of Spatial Decision Support Systems for Environmental Management

/ This paper describes a framework for designing spatial decision support systems for environmental management using a knowledge-based systems approach. An architecture for knowledge-based spatial decision supportsystems (KBSDSS) is presented that integrates knowledge-based systems with geographical information systems (GIS) and other problem-solving techniques. A method based on spatial influence diagrams is developed for representation of environmental problems. The spatial influence diagram provides an interface through which knowledge-based systems techniques can be applied to build capabilities for problem formulation, automated design, and execution of a solution process. In addition to the flexibility and developmental advantages of knowledge-based systems, the KBSDSS incorporates expert knowledge to provide assistance for structuring spatial influence diagrams and executing a solution process that automatically integrates the GIS, data base, knowledge base, and different types of models. The framework is illustrated with a system, known as the Islay Land Use Decision Support System (ILUDSS), designed to assist planners in strategic planning of land use for the development of the island of Islay, off the west coast of Scotland.KEY WORDS: Geographical information systems; Spatial decision support systems; Knowledge-based systems; Spatial influence diagrams; Environmental management

Journal Article↗

PubMed1992

A knowledge base of the chemical compounds of intermediary metabolism.

This paper describes a publicly available knowledge base of the chemical compounds involved in intermediary metabolism. We consider the motivations for constructing a knowledge base of metabolic compounds, the methodology by which it was constructed, and the information that it currently contains. Currently the knowledge base describes 981 compounds, listing for each: synonyms for its name, a systematic name, CAS registry number, chemical formula, molecular weight, chemical structure and two-dimensional display coordinates for the structure. The Compound Knowledge Base (CompoundKB) illustrates several methodological principles that should guide the development of biological knowledge bases. I argue that biological datasets should be made available in multiple representations to increase their accessibility to end users, and I present multiple representations of the CompoundKB (knowledge base, relational data base and ASN. 1 representations). I also analyze the general characteristics of these representations to provide an understanding of their relative advantages and disadvantages. Another principle is that the error rate of biological data bases should be estimated and documented-this analysis is performed for the CompoundKB.

Artificial Intelligence↗

PubMed2001

Knowledge-based inferencing after childhood head injury.

Inferencing was studied with a story comprehension task that required inferences to be made from a controlled knowledge base. Despite similar rates of knowledge base acquisition, knowledge base retention, and speeded access to the knowledge base across groups, the 18 children with severe head injury had lower rates of inferencing than the 15 children with mild head injury or the 18 age-matched controls. Results suggest that cognitive functions such as working memory and metacognitive skill that are disrupted by severe head injury may also play a role in some of the text- and discourse-level deficits commonly reported in these children, notably those involving inferencing.

Adolescent↗

PubMed1995

A knowledge-based system for diagnosis of mastitis problems at the herd level. 2. Machine milking.

A knowledge-based system for the diagnosis of mastitis problems at the herd level must search for possible causes, including malfunctioning milking machines or incorrect milking technique. A knowledge-based system on general mechanisms of mastitis infection, using hierarchical conditional causal models, was extended. Model building entailed extensive cooperation between the knowledge engineer and a domain expert. The extended knowledge-based system contains 12 submodels underlying the overview models. Nine submodels were concerned with mastitis problems arising from machine milking. These models are briefly described. The knowledge-based system has been validated by other experts after which the models were adjusted slightly. The final knowledge-based system was validated to data collected at 17 commercial dairy farms with high SCC in the bulk milk. Reports containing the farm data were accompanied by recommendations made by a dairy farm advisor. This validation showed good agreement between the knowledge-based system and the dairy farm advisors. The described knowledge-based system is a good tool for dairy farm advisors to solve herd mastitis problems caused by a malfunctioning milking machine or incorrect milking technique.

Animals↗

PubMed1990

A Prolog knowledge base for drug interactions.

This article describes a Prolog knowledge base for drug interactions. The knowledge base combines information from two databases: one of drug interactions and the second of drug chemical names and structures. Researchers can interrogate this knowledge base to answer questions about relationships between interacting drugs and their chemical components.

Artificial Intelligence↗

PubMed1993

Using the UMLS Semantic Network as a basis for constructing a terminological knowledge base: a preliminary report.

Sharing and reuse of knowledge bases is recognized in Artificial Intelligence and Medical Informatics as beneficial, but difficult. Reusing an existing knowledge base can save considerable time and effort during the knowledge engineering phase, and facilitates integration of systems. However, the degree to which knowledge can be shared among different applications is still mainly an empirical question. In this paper, we describe the preliminary results of our attempt to reuse the UMLS Semantic Network as an ontology for the knowledge base of a patient education system.

Algorithms↗

PubMed1998

An integrated approach for a knowledge-based clinical workstation: architecture and experience.

Today, the demand for medical decision support to improve the quality of patient care and to reduce costs in health services is generally recognized. Nevertheless, decision support is not yet established in daily routine within hospital information systems which often show a heterogeneous architecture but offer possibilities of interoperability. Currently, the integration of decision support functions into clinical workstations is the most promising way. Therefore, we first discuss aspects of integrating decision support into clinical workstations including clinical needs, integration of database and knowledge base, knowledge sharing and reuse and the role of standardized terminology. In addition, we draw up functional requirements to support the physician dealing with patient care, medical research and administrative tasks. As a consequence, we propose a general architecture of an integrated knowledge-based clinical workstation. Based on an example application we discuss our experiences concerning clinical applicability and relevance. We show that, although our approach promotes the integration of decision support into hospital information systems, the success of decision support depends above all on an adequate transformation of clinical needs.

Artificial Intelligence↗

PubMed1993

Automated integration of external databases: a knowledge-based approach to enhancing rule-based expert systems.

Expert system applications in the biomedical domain have long been hampered by the difficulty inherent in maintaining and extending large knowledge bases. We have developed a knowledge-based method for automatically augmenting such knowledge bases. The method consists of automatically integrating data contained in commercially available, external, online databases with data contained in an expert system's knowledge base. We have built a prototype system, named DBX, using this technique to augment an expert system's knowledge base as a decision support aid and as a bibliographic retrieval tool. In this paper, we describe this prototype system in detail, illustrate its use, and discuss the lessons we have learned in its implementation.

Artificial Intelligence↗

PubMed1992

Automated integration of external databases: a knowledge-based approach to enhancing rule-based expert systems.

Expert system applications in the biomedical domain have long been hampered by the difficulty inherent in maintaining and extending large knowledge bases. We have developed a knowledge-based method for automatically augmenting such knowledge bases. The method consists of automatically integrating data contained in commercially available, external, on-line databases with data contained in an expert system's knowledge base. We have built a prototype system, named DBX, using this technique to augment an expert system's knowledge base as a decision support aid and as a bibliographic retrieval tool. In this paper, we describe this prototype system in detail, illustrate its use and discuss the lessons we have learned in its implementation.

Asthma↗

PubMed1993

Comparing contents of a knowledge base to traditional information sources.

Physicians rely on the medical literature as a major source of medical knowledge and data. The medical literature, however, is continually evolving and represents different sources at different levels of coverage and detail. The recent development of computerized medical knowledge bases has added a new form of information that can potentially be used to address the practicing physician's information needs. To understand how the information from various sources differs, we compared the description of a disease found in the QMR knowledge base to those found in two general internal medicine textbooks and two specialized nephrology textbooks. The study shows both differences in coverage and differences in the level of detail. Textbooks contain information about pathophysiology and therapy that is not present in the diagnostic knowledge base. The knowledge base contains a more detailed description of the associated findings, more quantitative information, and a greater number of references to peer-reviewed medical articles. The study demonstrates that computerized knowledge bases, if properly constructed, may be able to provide clinicians with a useful new source of medical knowledge that is complementary to existing sources.

Artificial Intelligence↗

PubMed1993

Automatic knowledge base refinement: learning from examples and deep knowledge in rheumatology.

MESICAR is a second generation expert system which contains very general descriptions of rheumatological disorders in the primary medical care field. With the help of a detailed hierarchical description of the human anatomy the system is able to support diagnostic decisions. The paper describes how machine learning techniques are used to automatically construct more specific disease descriptions for common, frequently occurring cases. The system MESICAR-LEARN implements a learning method which integrates analytical and empirical learning techniques. Cases diagnosed by MESICAR form the training examples, and MESICAR's knowledge base is used as domain theory. The learned concepts are integrated into a hierarchy of disease descriptions. They support efficient and fast reasoning on common cases in addition to the general diagnostic support afforded by MESICAR's deep knowledge.

Algorithms↗

PubMed1990

Knowledge-based analysis and understanding of medical images.

Knowledge-based image analysis and interpretation of radiological images is of significant interest for several reasons including a means to identify and label each part of the image for further automated diagnostic analysis. Also, there is a need to develop a knowledge-based biomedical image analysis system which can analyze and interpret the anatomical images (such as those obtained from X-ray computed tomography (CT) scanning) in order to help analysis of functional images (such as those obtained from positron emission tomography (PET) scanning) of the organ of the same patient. This paper deals with the design and implementation of a knowledge-based system to analyze and interpret CT anatomical images of the human chest. In the approach presented here, the emphasis has been on the development of a strong low-level analysis system with the capability of analyzing in both bottom-up and top-down modes; and on the use of hierarchical relational, spatial, and structural knowledge of human anatomy in the process of high-level analysis and recognition.

Artificial Intelligence↗

PubMed1985

Effects of the knowledge base on children's memory strategies.

In this article, the importance of examining the linkage between knowledge and strategic factors in children's memory has been suggested. Indeed, it has been argued that a more complete analysis of the development of remembering in children requires a consideration of the operation of memory strategies in the context of the growing knowledge base. The effects of the knowledge base were analyzed in terms of concurrent influences on the use of strategies and long-term consequences for the development of increasingly skilled memory processing. The available evidence suggests that age-related changes in the contents of the knowledge system, as well as increases in the ease with which information can be accessed, contribute to the strategies that are used by children of different ages, and influence the development of efficient modes of processing. Continued research on the concurrent effects of the knowledge base should provide a more complete account of children's memory than that currently available, taking into consideration knowledge of the materials, understanding of the task demands, as well as overall strategic abilities. Similarly, research on the long-term developmental effects of the knowledge base on memory strategies should facilitate an understanding of the mechanisms by which memory processing becomes more efficient and less effortful. Ideally, studies that examine these issues should be longitudinal in scope (Ornstein et al., 1985a), but even cross-sectional research that explores the interrelationships between strategies and knowledge will facilitate an understanding of the development of memory in children.

Adolescent↗

PubMed1984

A comparison of LISP and MUMPS as implementation languages for knowledge-based systems.

Major components of knowledge-based systems are summarized, along with the programming language features generally useful in their implementation. LISP and MUMPS are briefly described and compared as vehicles for building knowledge-based systems. The paper concludes with suggestions for extensions to MUMPS that might increase its usefulness in artificial intelligence applications without affecting the essential nature of the language.

Computers↗

PubMed1991

Integration of an object knowledge base into a medical workstation.

A simple, yet powerful, knowledge base and its development environment is described that can act as a "knowledge server", integrated into a medical workstation. In many areas, such an integration of a knowledge base with other modules and systems is required, but difficult or impossible to achieve with existing commercial development shells. Three applications of the knowledge base are described: a controlled vocabulary for the classification of Congenital Heart Diseases, an extended data model for cardiology, and management of syntax descriptions for the BMDP command language.

Artificial Intelligence↗

PubMed1995

Knowledge-based potentials for proteins.

Knowledge based potentials and energy functions are extracted from a number of databases of known protein structures. Recent developments have shown that this type of potential is successful in many areas of protein structure research. Among these are quality assessment and error recognition of folds and the prediction of unknown structures by fold-recognition techniques.

Databases, Factual↗

PubMedDate not supplied

CKB - the compound knowledge base: a text based chemical search system.

The Compound Knowledge Base (CKB) was developed as a means of locating structures and additional relevant information from a given known structural identifier. Any of Chemical Abstracts Service Registry Number, company code (code number the producing company refers to the chemical entity internally), generic name (trivial or class name), or trade name (name under which the compound is marketed) can be provided as a query. CKB will provide the remaining available information as well as the corresponding structure for any matching compound in the database. The interface to the Compound Knowledge Base is Internet/World Wide Web-based, using Netscape Navigator and the ChemDraw Pro Plugin, which allows Merck scientists quick and easy access to the database from their desktop. The design and implementation of the database and the search interface are herein detailed.

Journal Article↗

PubMed2001

Knowledge-based interpretation of toxoplasmosis serology test results including fuzzy temporal concepts--the ToxoNet system.

Transplacental transmission of Toxoplasma gondii from an infected, pregnant woman to the unborn that occurs with a probability of about 60 percent [1] results in fetal damage to a degree depending on the gestational age. The computer system ToxoNet processes the results of serological antibody tests having been performed during pregnancy by means of a knowledge base containing medical knowledge on the interpretation of Toxoplasmosis serology tests. By applying this knowledge ToxoNet generates interpretive reports consisting of a diagnostic interpretation and recommendations for therapy and further testing. For that purpose it matches the results of all serological investigations of maternal blood with the content of the knowledge base returning complete textual interpretations for all given findings. The interpretation algorithm derives the stage of maternal infection from these that is used to infer the degree of fetal threat. To consider varying immune responses of particular patients, certain time intervals have to be kept between two subsequent tests in order to guarantee a correct interpretation of the test results. These time intervals are modelled as fuzzy sets, since they allow the formal description of the temporal uncertainties. ToxoNet comprises the knowledge base, an interpretation system, and a program for the creation and modification of the knowledge base. It is available from the World Wide Web by starting a standard browser like the Internet Explorer or the Netscape Navigator. Thus ToxoNet supports the physician in Toxoplasmosis diagnostics and in addition allows to adopt the way of making decisions to the characteristics of the particular laboratory by modifying the underlying knowledge base.

Algorithms↗