Design of a wearable device for real-time screening of urinary tract infection and kidney disease based on smartphone
Bibliographic record
Abstract
In this study, we developed a novel wearable and low-cost device for qualitative screening of glucose (GLU), leukocytes (LEU), and nitrite (NIT) and for semi-quantitative analysis of blood (BLD) and proteins (PRO) in the urine samples. The device can be attached to a diaper, and the results can be read by an app. The main functions of the device can be divided into sample collection, valve closing, and pad saturation; the recorded times for valve closing and pad saturation at four corners and pad saturation at the central parts are pseudo-medians (Hodges-Lehmann estimator) of 3.55 (95% WCI, 3.45-3.72), 6.5 (95% WCI, 6-7), and 6 (95% WCI, 5.5-6.5) minutes, respectively. The RGB values in the reagent pads remain stable from 20 min to 480 min, which satisfies the requirement of regular diaper-wearing time. Pre-diagnostic results indicate high accuracy with good accuracy for the app recognition of five biomarkers in the urine samples, which makes it a promising tool for screening diseases, especially for the elderly healthcare.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".