Name
Abstract | ||
|---|---|---|
Medical expert systems are designed to improve patient care by optimizing medical decision making. The distinguishing feature of medical expert systems is that they make recommendations based on input data; they are differentiated from decision support systems in that the latter are designed to help clinicians make decisions rather than actually make the recommendation, which is what an expert system does. This recommendation is essentially a prediction (of diagnosis or prognosis) or prescription (i.e., a treatment recommendation). The key issue in measuring the progress made thus far in medical expert systems is that of efficacy evaluation. For diagnostic or prognostic problems, the question is whether these systems have been able to predict more accurately than human experts. The literature suggests that expert systems are at least as accurate as human experts. For systems that make treatment recommendations, have medical expert systems truly improved patient outcomes? Again, it appears that validated expert systems make recommendations that are at least as good as those made by human experts, but the literature base is smaller. When trying to answer either of these questions, numerous issues need to be considered. |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1007/3-540-55930-2_11 | Logic Programming Summer School |
Keywords | DocType | Volume |
expert systems,information system,relational database management system,expert system | Conference | 636 |
ISSN | ISBN | Citations |
International Encyclopedia of Social & Behavioral Sciences | 3-540-55930-2 | 0 |
PageRank | References | Authors |
0.34 | 2 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lutz Plümer | 1 | 141 | 23.12 |