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Knowledge-based simulation of genetic regulation in bacteriophage lambda.

We have developed a general-purpose computer program for the functional simulation of regulatory genetics. This simulator is knowledge-based and was developed using the Unit System, a software tool for the acquisition, representation, and manipulation of hierarchically organized knowledge. The advantages of a knowledge-based design are presented, and the simulator's architecture is described. Its performance on the decision between lytic and lysogenic growth in Bacteriophage Lambda is reported.

Bacteriophage lambda↗

Paramedics: knowledge base and attitudes towards AIDS and hepatitis.

We surveyed 420 paramedics employed by a large metropolitan fire department to determine the effects of educational seminars on their knowledge base, perceptions, and attitudes about AIDS and hepatitis B. All surveys were completed on an anonymous, voluntary, and confidential basis. Our educational efforts improved the paramedics' knowledge base concerning the medical manifestations of AIDS, identification of risk factors, modes of transmission, and means of infection control, but had no impact on paramedics' fear of contracting AIDS. While paramedics have a strong fear of contracting AIDS, we note that they underestimate their risk of acquiring hepatitis B. Only 17% of paramedics surveyed had received the hepatitis vaccine, despite attending an infectious disease seminar addressing the occupational risks of acquiring hepatitis B infections during the previous year. Further educational efforts to address the paramedics' attitudes about AIDS, as well as to encourage paramedics to recognize hepatitis B exposure as a significant personal health risk, are currently being pursued.

Acquired Immunodeficiency Syndrome↗

A knowledge-based architecture for protein sequence analysis and structure prediction.

Methods for analyzing the amino-acid sequence of a protein for the purposes of predicting its three-dimensional structure were systematically analyzed using knowledge engineering techniques. The resulting entities (data) and relations (processing methods and constraints) have been represented within a generalized dependency network consisting of 29 nodes and over 100 links. It is argued that such a representation meets the requirements of knowledge-based systems in molecular biology. This network is used as the architecture for a prototype knowledge-based system that simulates logically the processes used in protein structure prediction. Although developed specifically for applications in protein structure prediction, the network architecture provides a strategy for tackling the general problem of orchestrating and integrating the diverse sources of knowledge that are characteristic of many areas of science.

Amino Acid Sequence↗

Knowledge-based bioterrorism surveillance.

An epidemic resulting from an act of bioterrorism could be catastrophic. However, if an epidemic can be detected and characterized early on, prompt public health intervention may mitigate its impact. Current surveillance approaches do not perform well in terms of rapid epidemic detection or epidemic monitoring. One reason for this shortcoming is their failure to bring existing knowledge and data to bear on the problem in a coherent manner. Knowledge-based methods can integrate surveillance data and knowledge, and allow for careful evaluation of problem-solving methods. This paper presents an argument for knowledge-based surveillance, describes a prototype of BioSTORM, a system for real-time epidemic surveillance, and shows an initial evaluation of this system applied to a simulated epidemic from a bioterrorism attack.

Artificial Intelligence↗

Integrating a modern knowledge-based system architecture with a legacy VA database: the ATHENA and EON projects at Stanford.

We present a methodology and database mediator tool for integrating modern knowledge-based systems, such as the Stanford EON architecture for automated guideline-based decision-support, with legacy databases, such as the Veterans Health Information Systems & Technology Architecture (VISTA) systems, which are used nation-wide. Specifically, we discuss designs for database integration in ATHENA, a system for hypertension care based on EON, at the VA Palo Alto Health Care System. We describe a new database mediator that affords the EON system both physical and logical data independence from the legacy VA database. We found that to achieve our design goals, the mediator requires two separate mapping levels and must itself involve a knowledge-based component.

Artificial Intelligence↗

The effect of experimental resolution on the performance of knowledge-based discriminatory functions for protein structure selection.

The key to an accurate method of protein structure prediction is the development of an effective discriminatory function. Knowledge-based discriminatory functions extract parameters from statistical analysis of experimentally determined protein structures. We assess how the quality of the protein structures used for compiling statistics affects the performance of a residue-specific all-atom probability discriminatory function (RAPDF). We find that the discriminatory power correlates with the quality of the structural dataset on which the RAPDF is parameterized in a statistically significant manner. The overrepresentation of unfavorable contacts in the low-resolution and NMR structures contributes to the major errors in the compilation of the conditional probabilities. Such errors weaken the discriminatory power of the function, especially when decoy conformations also contain considerable numbers of unfavorable contacts. This indicates that using high-resolution structural datasets after filtering out unfavorable contacts can improve the performance of knowledge-based discriminatory functions.

Computational Biology↗

A knowledge-based system for cassette mutagenesis experimental design.

A knowledge-based system for the design and planning of cassette mutagenesis experiments has been developed for scientists working in the field of structural biology and protein engineering. The system applies domain-specific knowledge to manage the menial details and automate most of the decision-making steps involved in the design process. This allows scientists to work at a high abstraction level, and results in significant time savings and increased productivity. The system also includes an automated documentation facility to improve the efficiency and accuracy of record keeping.

Artificial Intelligence↗

Riding the storms--approaching cardiac intervention: combining an information-based managerial perspective with a knowledge-based expert view.

To contribute to an improvement of efficiency within the health care system, it is important for each medical professional involved in a specific value chain of cure to have some basic understanding of the related and updated treatment methods. In a relatively short time, the field of interventional cardiology has evolved into an independent clinical discipline with a wide variety of therapeutic modalities. At present, it is possible to safely treat lesions in the main stem of the left coronary artery with percutaneous transluminal angioplasty. The risk of thrombosis and restenosis following stent delivery has been significantly reduced by the introduction of several new pharmacological agents and improvement in the design of the stents. In addition, it has been confirmed that primary angioplasty in acute myocardial infarction has a superior outcome compared with thrombolysis. The aforementioned historical overview is highlighted from an integrated managerial and clinical perspective.

Angioplasty, Balloon, Coronary↗

Integrated knowledge-based functions in a hospital cancer registry--specific requirements for routine applicability.

The background of the presented work is the design, realization, and routine use of integrated knowledge-based functions in the context of a hospital cancer registry. The first field of application was supporting registrars to detect data inconsistencies and incompleteness timely during the documentation process. Especially, we focused on the acceptance of the administrator of the underlying information system and on the phenomenon of duplicate and outdated messages. These aspects are specific for integrated knowledge based functions and a precondition for obtaining a routine applicability and acceptance.

Artificial Intelligence↗

Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. II. Evaluation of diagnostic performance.

We have developed a probabilistic reformulation of the Quick Medical Reference (QMR) system. In Part I of this two-part series, we described a two-level, multiply connected belief-network representation of the QMR knowledge base and a simulation algorithm to perform probabilistic inference on the reformulated knowledge base. In Part II of this series, we report on an evaluation of the probabilistic QMR, in which we compare the performance of QMR to that of our probabilistic system on cases abstracted from continuing medical education materials from Scientific American Medicine. In addition, we analyze empirically several components of the probabilistic model and simulation algorithm.

Algorithms↗

Reification of abstract concepts to improve comprehension using interactive virtual environments and a knowledge-based design: a renal physiology model.

Several abstract concepts in medical education are difficult to teach and comprehend. In order to address this challenge, we have been applying the approach of reification of abstract concepts using interactive virtual environments and a knowledge-based design. Reification is the process of making abstract concepts and events, beyond the realm of direct human experience, concrete and accessible to teachers and learners. Entering virtual worlds and simulations not otherwise easily accessible provides an opportunity to create, study, and evaluate the emergence of knowledge and comprehension from the direct interaction of learners with otherwise complex abstract ideas and principles by bringing them to life. Using a knowledge-based design process and appropriate subject matter experts, knowledge structure methods are applied in order to prioritize, characterize important relationships, and create a concept map that can be integrated into the reified models that are subsequently developed. Applying these principles, our interdisciplinary team has been developing a reified model of the nephron into which important physiologic functions can be integrated and rendered into a three dimensional virtual environment called Flatland, a virtual environments development software tool, within which a learners can interact using off-the-shelf hardware. The nephron model can be driven dynamically by a rules-based artificial intelligence engine, applying the rules and concepts developed in conjunction with the subject matter experts. In the future, the nephron model can be used to interactively demonstrate a number of physiologic principles or a variety of pathological processes that may be difficult to teach and understand. In addition, this approach to reification can be applied to a host of other physiologic and pathological concepts in other systems. These methods will require further evaluation to determine their impact and role in learning.

Comprehension↗

The performance of the knowledge-based system VALAB revisited: an evaluation after five years.

In 1988, inundated by the tedious work of validation of laboratory reports in a large hospital biochemistry laboratory, we designed VALAB, a knowledge-based system specially dedicated to this iterative function. Coping at first with a few biochemical tests, the program has been progressively expanded to forty-five common chemical tests. Simultaneously some new rules have been introduced to "weight" the conclusion in different circumstances and rules taking into consideration some clinical data have also been written. Moreover the program moved to other disciplines, pH and blood gases, haematology and coagulation. Accordingly the evaluation protocol has been modified, incorporating a new step, the consensus decision of the pathologists, operating within the initial protocol and based upon the various criteria of epidemiology. These major changes and improvements have led us to check and describe again the performance of this updated VALAB knowledge-based system.

Artificial Intelligence↗

A menu-driven knowledge base browsing tool.

Conventional computer-assisted medical decision-making systems have had limited impact on routine clinical practice. This has stimulated an alternative approach to the utilization of medical knowledge bases. Centering on the storage and retrieval of medical information, it aims to provide clinicians with computerized medical reference systems. In this paper we describe the development of a prototype menu-driven browsing tool, which allows clinicians to browse through the contents of a knowledge base in a number of ways. Operations include interrogation via disease classes, names or attributes; hierarchical display of all or part of a disease profile; printing of a disease profile; construction of differential diagnosis lists and comparison of two diseases. We discuss how the use of a menu-driven interface can help to overcome some of the problems encountered with previous designs of medical reference systems.

Artificial Intelligence↗

Knowledge-based vision and simple visual machines.

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong.

Animals↗

A knowledge-based approach to the deflocculation problem: integrating on-line, off-line, and heuristic information.

A knowledge-based approach for the supervision of the deflocculation problem in activated sludge processes was considered and successfully applied to a full-scale plant. To do that, a methodology that integrates on-line, off-line and heuristic information has been proposed. This methodology consists of three steps: (i). development of a decision tree (which involves knowledge acquisition and representation); (ii). implementation into a rule-based system; and (iii). validation. The set of symptoms most useful in diagnosing the deflocculation problem has been identified, the different branches to diagnose pin-point floc and dispersed growth have been built (using generic and specific knowledge), and all this knowledge has been codified into an object-oriented shell. The results obtained in the application of this knowledge-based approach to the Granollers WWTP (which treats about 130000 inhabitants-equivalents) showed that the system was able to identify correctly the problem with reasonable accuracy. Our positive experience building this system suggests that this approach is a practical and valuable element to include in an intelligent supervisory system combining numerical and reasoning techniques.

Artificial Intelligence↗

Providing concept-oriented views for clinical data using a knowledge-based system: an evaluation.

OBJECTIVE: Clinical information systems typically present patient data in chronologic order, organized by the source of the information (e.g., laboratory, radiology). This study evaluates the functionality and utility of a knowledge-based system that generates concept-oriented views (organized around clinical concepts such as disease or organ system) of clinical data. DESIGN: The authors have developed a system that uses a knowledge base of interrelationships between medical concepts to infer relationships between data in electronic medical records. They use these inferences to produce summaries, or views, of the data that are relevant to a specific concept of interest. They evaluated the ability of the system to select relevant information, reduce information overload, and support physician information retrieval. MEASUREMENTS: The sensitivity and specificity of the system for identifying relevant patient information were calculated. Effect on information overload was assessed by comparing the amount of information in each view with the amount of information in the entire record. Information retrieval accuracy and cost (time) were used to measure the effect of using concept-oriented views on the efficiency and effectiveness of retrievals. RESULTS: The sensitivity and specificity of the system for identifying relevant clinical information were generally in the range of 70 to 80 percent. Concept-oriented views are effective in reducing the amount of information retrieved (over 80 percent reduction) and, compared with source-oriented views, are able to improve physician retrieval accuracy (p=0.04). CONCLUSION: Computer-generated, concept-oriented views can be used to reduce clinician information overload and improve the accuracy of clinical data retrieval.

Artificial Intelligence↗

Toward a medical linguistic knowledge base.

This paper presents the design of a Medical Linguistic Knowledge Base (MLKB). This MLKB is intended to be the multilingual recipient for all the declarative knowledge about languages. It includes words, their syntax and their conceptual representation, typology of concepts of the domain, rules for semantic analysis and conceptual schemata. For that purpose, Sowa's conceptual graphs are considered as an adequate knowledge representation. The MLKB will be an enormous body of information, and the difficulty to feed it and to validate it appears immediately. Therefore, it is necessary to start an international initiative to merge efforts from different groups.

Language↗

Requirements for an on-line knowledge-based anatomy information system.

User feedback from the Digital Anatomist Web-based anatomy atlases, together with over 20 years of anatomy teaching experience, were used to formulate the requirements and system design for a next-generation anatomy information system. The main characteristic of this system over current image-based approaches is that it is knowledge-based. A foundational model of anatomy is accessed by an intelligent agent that uses its knowledge about the available anatomy resources and the user types to generate customized interfaces. Current usage statistics suggest that even partial implementation of this design will be of great practical value for both clinical and educational needs.

Anatomy, Artistic↗