Computer Aided Diagnosis – A Review of Research

Abstract

Computer aided diagnosis is reviewed and an assessment made of the different models used for this purpose. These are discussed under three headings:1. Models based on physicians’ thought processes2. Models based on the physiological relationships manifested in the disease state,3. Statistical models.The models are assessed in terms of their accuracy by comparison with clinical methods. Typical results show that using the computer improves diagnostic accuracy by about 10%.It is concluded that Bayesian models are likely to give the best results since they are well suited to the probabilistic nature of medical data and can be adapted for use in many situations. Further research necessary for the improvement of Bayesian models is discussed.

Statistical and Knowledge-Based Approaches to Clinical Decision-Support Systems, with an Application in Gastroenterology

“…A wide range of medical problems have been attacked by "computer-aided diagnosis", as it is usually known. Wagner et al (1978) provide a bibliography of over 800 references up to 1977, although since then applications have been decreasing steadily: Index Medieus cited 30 papers under "Diagnosis: Computer-assisted" in 1982Computer-assisted" in compared with 83 in 1977 In this section we have only space to give some examples of the type of statistical models that have been found useful; for further reviews see Patrick et al (1974), Wardle and Wardle (1978), Rogers et al (1979), Shortliffe et al (1979) and Titterington et al (1981).…”

Knowledge engineering for medical decision making: A review of computer-based clinical decision aids

“…In this article we review several medical decision making paradigms and discuss some issues that account for both the multip licity of approaches and the limited clinical success of most systems developed to date. Because other authors have reviewed computer-aided diagnosis [47], (92], (114] and the potential impact of computers in medical care [93], our emphasis here is somewhat different. We will focus on the symbolic representation and use of knowledge , termed "knowledge engineering ," and the inadequacies of data-intensive techniques which have led to the exploration of novel symbolic reasoning approaches during the last decade.…”

“…• Thus the motivations for attempts to understand and automate the process of clinical decision making have been numerous (114). They are directed both at diagnostic models and at assisting with patient management decisions .…”

A structural model of the impact of physicians' perceptions of computers on the use of hospital information systems

“…Yet there is a serious gap in the utilization of the systems by physicians (Friedman and Gustafson 1977, Laska and Abbey 1980, Wardle and Wardle 1978. General resistance to innovation cannot explain the limited spread of clinical computing systems.…”