Prototype Development of Continuous Remote Monitoring of ICU Patients at Home
Bibliographic record
Abstract
Vital signs are a group of essential body parameter, which provides the overall health state of a human body. They often play a pivotal role in accessing the overall physiological state of the human body. For patients requiring intense and continuous monitoring, especially those in an Intensive Care Unit, the essentiality to assess their vital signs regularly. Monitoring the health status of ICU patients becomes quite cost-effective when the same can be monitored within the comfort zone of their own house. The technique elaborated herein revolves around the fundamental idea of implementing a vital sign monitoring system that continuously assesses a patient and regularly updates the same to a centralized server system. In an event of a medical emergency, the relevant data is conveyed to the doctor via an efficient alert system, thereby ensuring safe and timely treatment to the patients. Also, as suggested the proposed design is characterized by IoT capability that allows real-time monitoring of the subject, thereby allowing, minimizing the human involvement in its operation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".