The application of expert systems in parenteral nutrition

Total Parenteral Nutrition (TPN) is a medical technique used to provide a patient\u27s nutritional requirements via intravenous feeding. Critically ill patients must have adequate nutrition but must also have a stable physiology compensated for or treated by drugs. Several factors such as the complex nature of the TPN solution, the cost of the ingredients and the possible interaction of nutrient and drugs has led to the development of small expert system to assist the hospital medical staff in formulating the TPN constituents and assist the pharmacy staff in producing the final solution. This text will describe a small knowledge-based diagnostic system which when combined with conventional programming techniques has led to tangible benefits within a hospital Intensive Care Unit and Pharmacy

Expert Systems as Overlapping Logical Theories

Abstract We discuss the model-theoretic characterization of the components of logic-based expert systems which employ pure meta-level inference regimes. The roles of the basic components of such systems in the underlying fust order theories are specified. This includes the domain specific rules, meta-level inference engine, and intrinsic interpreter. Fragments of an actual expert system are used to motivate and illustrate the analysis

The development of an expert system shell with a mixed knowledge representation, explicit control of reasoning and a truth maintenance system

Bibliography: pages 227-236.This thesis concentrates on several important issues in expert system research, namely - representation of knowledge - control of reasoning - implementation of non-monotonic logics via truth maintenance systems. There are three parts to this thesis. PART1 covers the background research in the above mentioned topics. PART2 discusses the WISE system and the way in which research from PART1 was applied to the development of the WISE shell. PART3 considers the features of other expert system shells

A study of the methodologies currently available for the maintenance of the knowledge-base in an expert system

This research studies currently available maintenance methodologies for expert system knowledge bases and taxonomically classifies them according to the functions they perform. The classification falls into two broad categories. These are: (1) Methodologies for building a more maintainable expert system knowledge base. This section covers techniques applicable to the development phases. Software engineering approaches as well as other approaches are discussed. (2) Methodologies for maintaining an existing knowledge base. This section is concerned with the continued maintenance of an existing knowledge base. It is divided into three subsections. The first subsection discusses tools and techniques which aid the understanding of a knowledge base. The second looks at tools which facilitate the actual modification of the knowledge base, while the last secttion examines tools used for the verification or validation of the knowledge base. Every main methodology or tool selected for this study is analysed according to the function it was designed to perform (or its objective); the concept or principles behind the tool or methodology: and its implementation details. This is followed by a general comment at the end of the analysis. Although expert systems as a rule contain significant amount of information related to the user interface, database interface, integration with conventional software for numerical calculations, integration with other knowledge bases through black boarding systems or network interactions, this research is confined to the maintenance of the knowledge base only and does not address the maintenance of these interfaces. Also not included in this thesis are Truth Maintenance Systems. While a Truth Maintenance System (TMS) automatically updates a knowledge base during execution time, these update operations are not considered \u27maintenance\u27 in the sense as used in this thesis. Maintenance in the context of this thesis refers to perfective, adaptive, and corrective maintenance (see introduction to chapter 4). TMS on the other hand refers to a collection of techniques for doing belief revision (Martin, 1990) . That is, a TMS maintains a set of beliefs or facts in the knowledge base to ensure that they remain consistent during execution time. From this perspective, TMS is not regarded as a knowledge base maintenance tool for the purpose of this study

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming

New Models for Expert System Design

This thesis presents new work on the analysis of human lung sound. Experimental studies investigated the relationship between the condition of the lungs and the power spectrum of lung sound detected at the chest wall. The conclusion drawn from two clinical studies was that the median frequency of the lung sound power spectrum increases with a decrease in airway calibre. The technique for the analysis of lung sound presented in this thesis is a non-invasive method which may be capable of assessing differences in airway calibre between different lobes of the lung. An expert system for the analysis of lung sound data and pulmonary function data was designed. The expert knowledge was expressed in a belief logic, a system of logic which is more expressive than first order logic. New automated theorem proving methods were developed for the belief logic. The new methods were implemented to form the 'inference engine' of the expert system. The new expert system compared favourably with systems which perform a similar task. The use of belief logic allows introspective reasoning to be carried out. Plausible reasoning, a type of introspective reasoning which allows conclusions to be drawn when the database is incomplete, was proposed and tested. The author concludes that the use of a belief logic in expert system design has significant advantages over conventional approaches. The experimental results of the lung sound research were incorporated into the expert system rule base: the medical and expert system research were complementary

A methodology for the design, implementation and evaluation of intelligent systems with an application to critical care medicine

This thesis illustrates the technology required to provide a new generation of clinical instrumentation systems for critical care medicine. This advance in measurement science is gained from the use of a knowledge-based component able to process information as well as data. To implement a clinical information system using knowledge-based technology requires prior knowledge of human and computer-based activity within the critical domain. A historical perspective is given to both of these topics which reflects the genesis of current practice. The application area is introduced by investigating a control system approach to managing patients who require ventilatory therapy. It was found that no current methodology is wholly appropriate when a knowledge-based component is included in the technological paradigm. Therefore, a novel methodology for system design, implementation and evaluation is proposed, and its utility tested in the aforementioned application domain. The detailed processes involved in the evolution of a prototype system which aids the clinical user in the art of ventilatory therapy are shown. Three levels of machine intelligence are shown to be required, based on: context-sensitive deterministic mechanisms; pattern cognition; and decision support elements. A wider discussion of the important points raised in the practical use of the methodology focuses upon the philosophical basis of clinical information systems and the processes of knowledge elicitation, knowledge representation and intelligent system evaluation

Information technology and distance learning aspects of materials databases

Distance learning is a flourishing area, with the number of programs, provided via remote delivery, increasing daily. At the same time, however, progress in the field of accessibility and support for learners, who want to pursue education and training in the area of materials science and engineering, has not always kept pace. An individual interested in taking a materials course, or in simply finding out what is available, may find himself/herself forced to locate and then plough through many unwieldy online course listings. This may discourage many learners from pursuing the distance learning option. In recent years, more and more distance learning databases have been developed and made available on the World Wide Web. These distance-learning databases are aimed to offer an information pool on many courses and programs that are available online and to cater for users' specific needs of locating information. This need is equally applicable to the area of materials science and engineering. The purpose of this current research has been to explore Information and Technology aspects of materials databases and closely study distance learning aspects. [Continues.