Name
Abstract | ||
|---|---|---|
A prototype Medical Decision Support System (MDSS) for leukemia patients was developed with emphasis on total management approach from patient registration to diagnosis and treatment. Thus, the MDSS consists of four modules: registry, knowledge model, simulator, and Computer-Assisted Instruction (CAI). Integration of each module improves overall patient management capability and knowledge acquisition capability of the system. Four different knowledge models were developed to predict diagnosis: rule-based reasoning, case-based reasoning, neural network, and discriminant analysis. Among the four, rule-based reasoning produced the most accurate prediction in diagnosis. In the future, the method of leukemia registry can further be extended to the hospital-based cancer registry for other types of cancer. In order to be more effective, the registry should also be integrated with the hospital information system for an easier data entry. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1016/S0957-4174(98)00040-2 | Expert Systems with Applications |
Keywords | Field | DocType |
rule based reasoning,discriminant analysis,neural network,case base reasoning | Data mining,Patient registration,Computer science,Decision support system,Model-based reasoning,Artificial intelligence,Linear discriminant analysis,Artificial neural network,Hospital information system,Machine learning,Cancer registry,Knowledge acquisition | Conference |
Volume | Issue | ISSN |
15 | 3-4 | 0957-4174 |
Citations | PageRank | References |
5 | 0.46 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Young Moon Chae | 1 | 69 | 11.23 |
| Quehn Park | 2 | 5 | 0.46 |
| Kwang Su Park | 3 | 5 | 0.46 |
| Mi Young | 4 | 5 | 0.46 |