Abstract
A knowledge-based decision support system to interpret online flow cytometry results for hematologic malignacies has been developed in this study as a complete client-server application. The list mode data files are loaded to the system where gating, dot plot, histogram and contour plot have been performed. Upon gating, the CD marker results are generated as a percentage with associated positive or negative designation. Differential diagnosis with different confidence levels is generated based on a semantic network of knowledge base embedded in an extensible mark up language (XML). Java programming is used to implement the inference engine where tree structure and search algorithm are employed. A set of 273 flow cytometry list mode data files are fed into the system and diagnosis was correctly included in top three differential diagnoses in 94% of all cases tested.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 109-124 |
| Number of pages | 16 |
| Journal | International Journal of Medical Engineering and Informatics |
| Volume | 1 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2008 |
| Externally published | Yes |
Keywords
- CD markers
- client-server technology
- clinical decision support system
- flow cytometry
- hematologic disease
- immunophenotyping
- knowledge base
- list mode
ASJC Scopus subject areas
- Medicine (miscellaneous)
- Biomaterials
- Biomedical Engineering
- Health Informatics