This review looks at a variety of different ways in which computers can be used to assist in the interpretation of radiological images and in radiological decision-making. The issues involved in the design of computerized decision aids are introduced and four criteria proposed for evaluating such aids: need, practicality, veracity and relevance. These criteria are used to assess research into decision aids based on: image databases, numerical methods, expert systems, image processing and image understanding systems. Possible directions for research leading to aids of practical value are discussed in the conclusion.

Invited review: computer aids for decision-making in diagnostic radiology--a literature review.

Extensive amounts of knowledge and data stored in medical databases request the development of specialized tools for storing and accessing of data, data analysis, and effective use of stored knowledge and data. This paper focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension. The paper sketches the history of research that led to the development of current intelligent data analysis techniques, discusses the need for intelligent data analysis in medicine, and proposes a classification of intelligent data analysis methods. The main scope of the paper are machine learning and temporal abstraction methods and their application in medical diagnosis. A selection of methods and diagnostic domains is presented, and the performance and usefulness of approaches discussed. The paper concludes with the evaluation of selected intelligent data analysis methods and their applicability in medical diagnosis.

Intelligent data analysis for medical diagnosisc using machine learning and temporal abstraction

Temporal diagnostic reasoning based on time-objects.

Describes challenges in using image processing and automated feature extraction for improving diagnostic accuracy. The generalization of digital technology in medical imaging makes it possible to design computer-aided decision-support tools to help resolve the difficulties encountered by radiologists. It has already been demonstrated that image processing and automated feature extraction can help improve diagnostic accuracy in some applications. Future challenges are for the development of vision techniques tailored for a wider range of imaging modalities and pathologies the design of methods for the combination of several classifiers, and the implementation of expert systems incorporating both low-level feature extractors and high-level clinical knowledge. After evaluation, these tools will be integrated in PACS systems to highlight regions of interest and to provide clinicians with a documented second opinion. Then, such integrated systems can be used routinely in the clinical practice and teaching of radiology.

Computerized decision support in medical imaging

In temporal reasoning there are two interrelated issues; how to model time per se and how to model occurrences. In medical temporal reasoning the need for multiple granularities and multiple conceptual temporal contexts arises in relation to a model of time. Some occurrence can then be expressed with respect to different temporal contexts. This paper presents a multidimensional and multigranular model of time for knowledge-based problem solving, primarily for medical applications. Both the conceptual issues and the design issues underlying the implementation of the proposed model are discussed. The presented model of time has been developed in the context of a time ontology for medical knowledge engineering, whose principal primitives are the time-axis and the time-object. The notion of a time-axis constitutes the primitive for the proposed model of time, while the notion of a time-object aims to integrate time with other essential forms of knowledge, such as structural and causal knowledge, in the expression of different types of occurrences, thus resulting in the integral embodiment of time in such occurrences. The notion of a time-object and the overall ontology of occurrences is given only a cursory mention in this paper. The focus of the paper is the time model. More specifically, the paper presents the notion of a time-axis in the context of the overall time ontology and discusses at length the two classes of time-axes, namely the atomic axes and the spanning axes. The assertion language which has been developed, for the entire ontology, for the expression of axioms (deductive rules and integrity constraints), attribute constraints and propagation methods is presented and illustrated. The implementation of the time model in terms of a layered object-based system is also presented.

A Multidimensional and Multigranular Model of Time for Medical Knowledge-Based Systems

Modelling diagnostic skills in the domain of skeletal dysplasias

http://www.cs.ucy.ac.cy/~elpida/docs/BackgroundKnowledge.pdf

Background knowledge in diagnosis

Expert systems are consultative, highly interactive systems, and hence the quality of interaction between system and user is important for the acceptability of the system. Acquisition of data about the problem in hand is a central feature of the interaction between system and user, and it makes a major contribution to the user's perception of the system. It is therefore crucial that the acquisition of this data (both as individual data items and as a sequence of data inputs) is perceived by the user as competent.

This paper identifies central, domain-independent, design goals for the information-acquisition interactions between an expert system and its user, including mixed-initiative interaction, flexibility in user input, and system competence in querying the user. The paper discusses the realisation of these goals in a diagnostic expert system, Skeletal Dysplasias Diagnostician, through an explicit data model which allows for the representation of data with temporal and spatial (locality) aspects and the decide-status function which operates on the data model.

/pdf/towards-competent-information-acquisition-interactions-1x67ck1grh.pdf

F. Dams

Papers

Modelling diagnostic skills in the domain of skeletal dysplasias

Background knowledge in diagnosis

Towards competent information acquisition interactions between an expert system and its user