Development process of multiagent system for glycemic control of intensive care unit patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article presents the entire process of developing an agent-based system for the glycemic control of patients in the Intensive Care Unit (ICU). The agent’s goal is to monitor and recommend treatment to keep the patient’s blood glucose within the target range, avoiding complications in the health of patients and even decreasing rates of morbidity and mortality in the ICU. The process of developing the agent-based solution was presented, starting from the understanding of the problem, including a brief review of the literature, going through the pre-project and modelling through the Tropos methodology, until the implementation. The agent inference mechanism is based on production rules and intuitionistic fuzzy logic. An illustration of use, with the collaboration of a specialist intensive care physician, shows how agents behave in a real situation of monitoring and controlling the blood glucose of patients admitted to the ICU, interacting with all elements of the proposed architecture. Finally, feedback from health professionals indicate the system can assist in the glycemic control of patients in the ICU having advantages over traditional monitoring systems.
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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 | 0.002 |
| 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 | 0.000 |
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 it