Glucose monitoring measuring blood glucose using vertical cavity surface emitting lasers (VCSELs)
Bibliographic record
Abstract
Diabetes Mellitus is a common chronic disease that is an ever-increasing public health issue. Continuous glucose monitoring has been shown to help diabetes mellitus patients stabilize their glucose levels, leading to improved patient health. Hence, a glucose sensor, capable of continuous real-time monitoring, has been a topic of research for three decades. Current methods of glucose monitoring, however, require taking blood samples several times a day, hence patient compliance is an issue. Optical methods are one of the painless and promising methods that can be used for blood glucose predictions. However, having accuracies lower than what is acceptable clinically has been a major concern. To improve on the accuracy of the predictions, the signal-to-noise ratio in the spectrum can be increased, for which the use of thermally tunable vertical cavity surface emitting lasers (VCSELs) as the light source to obtain blood absorption spectra, along with a multivariate technique (Partial Least Square (PLS) techniques) for analysis, is proposed. VCSELs are semiconductor lasers with small dimensions and low power consumption, which makes them suitable for implants. VCSELs provide higher signal-to-noise ratio as they have high power spectral density and operate within a small spectrum. In the current research, experiments were run for the preliminary investigations to demonstrate the feasibility of the proposed technique for glucose monitoring. This research involves preliminary investigations for developing a novel optical system for accurate measurement of glucose concentration. Experiments in aqueous glucose solutions were designed to demonstrate the feasibility of the proposed technique for glucose monitoring. In addition, multivariate techniques, such as PLS, were customized for various specific purposes of this project and its preliminary investigation. This research will lead to the development of a small, low power, implantable optical sensor for diabetes patients, which will be a major breakthrough in the area of treating diabetes patients, upon successful completion of this research and development of the device.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".