Incorporating Game-Theoretic Rough Sets in Web-Based Medical Decision Support Systems
Bibliographic record
Abstract
Web-based support systems (WSS) assist human activities with the modern Web technology. An important branch of WSS is Web-based decision support systems that provide intelligent support for decision making tasks. We focus on decision making in Web-based medical decision support systems (WMDSS) that can provide support for making diagnosis and treatment decisions. The use of game-theoretic rough set (GTRS) component in WMDSS is explored and investigated for this purpose. The GTRS is a recent development in rough sets that takes advantages from data analysis capabilities of rough sets complimented with decision analysis abilities of game theory. The GTRS may be used to obtain rough sets based three-way or ternary decisions by determining a pair of threshold values. Demonstrative example suggests that the GTRS may be considered as an alternative decision making model and component in building WMDSS for providing decision support.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".